Agilent Feature Extraction 12.2 Microarray Reference Guide PDF

Agilent Technologies

Agilent Feature Extraction 12.2

Reference Guide For Research Use Only. Not for use in diagnostic procedures.

2 Feature Extraction Reference Guide

Notices Agilent Technologies, Inc. 2021

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Revision A0, January 2021

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Feature Extraction Reference Guide 3

In This Guide This Reference Guide contains tables that list default parameter values and results for Feature Extraction analyses, and explanations of how Feature Extraction uses its algorithms to calculate results.

1 Protocol Default Settings

This chapter includes tables that list the default parameter values found in the protocols shipped with the software (Agilent 2- color gene expression (GE), 1- color GE, CGH, ChIP, miRNA and non- Agilent protocols).

2 QC Report Results

Learn how to read and interpret the QC Reports.

3 Text File Parameters and Results

This chapter contains a listing of parameters and results within the text file produced after Feature Extraction.

4 XML (MAGE-ML) Results

Refer to this chapter to find the results contained in the MAGE- ML files generated after Feature Extraction.

5 How Algorithms Calculate Results

Learn how Feature Extraction algorithms calculate the results that help you interpret your gene expression (2- color and 1- color), CGH, ChIP and miRNA experiments.

6 Command Line Feature Extraction

This chapter contains the commands and arguments to integrate Feature Extraction into a completely automated workflow.

4 Feature Extraction Reference Guide

Acknowledgments

Apache acknowledgment

Part of this software is based on the Xerces XML parser, Copyright (c) 1999- 2000 The Apache Software Foundation. All Rights Reserved (www.apache.org).

JPEG acknowledgment

This software is based in part on the work of the Independent JPEG Group. Copyright (c) 1991- 1998, Thomas G. Lane. All Rights Reserved.

Loess/Netlib acknowledgment

Part of this software is based on a Loess/Lowess algorithm and implementation. The authors of Loess/Lowess are Cleveland, Grosse and Shyu. Copyright (c) 1989, 1992 by AT&T. Permission to use, copy, modify and distribute this software for any purpose without fee is hereby granted, provided that this entire notice in included in all copies of any software which is or includes a copy or modification of this software and in all copies of the supporting documentation for such software.

THIS SOFTWARE IS BEING PROVIDED AS IS, WITHOUT ANY EXPRESS OR IMPLIED WARRANTY. NEITHER THE AUTHORS NOR AT&T MAKE ANY REPRESENTATION OR WARRANTY OF ANY KIND CONCERNING THE MERCHANTABILITY OF THIS SOFTWARE OR ITS FITNESS FOR ANY PARTICULAR PURPOSE.

Stanford University School of Medicine acknowledgment

Non- Agilent microarray image courtesy of Dr. Roger Wagner, Division of Cardiovascular Medicine, Stanford University School of Medicine

Ultimate Grid acknowledgment

This software contains material that is Copyright (c) 1994- 1999 DUNDAS SOFTWARE LTD., All Rights Reserved.

Feature Extraction Reference Guide 5

LibTiff acknowledgement

Part of this software is based upon LibTIFF version 3.8.0.

Copyright (c) 1988- 1997 Sam Leffler Copyright (c) 1991- 1997 Silicon Graphics, Inc.

Permission to use, copy, modify, distribute, and sell this software and its documentation for any purpose is hereby granted without fee, provided that (i) the above copyright notices and this permission notice appear in all copies of the software and related documentation, and (ii) the names of Sam Leffler and Silicon Graphics may not be used in any advertising or publicity relating to the software without the specific, prior written permission of Sam Leffler and Silicon Graphics.

THE SOFTWARE IS PROVIDED AS- IS AND WITHOUT WARRANTY OF ANY KIND, EXPRESS, IMPLIED OR OTHERWISE, INCLUDING WITHOUT LIMITATION, ANY WARRANTY OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE.

IN NO EVENT SHALL SAM LEFFLER OR SILICON GRAPHICS BE LIABLE FOR ANY SPECIAL, INCIDENTAL, INDIRECT OR CONSEQUENTIAL DAMAGES OF ANY KIND, OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER OR NOT ADVISED OF THE POSSIBILITY OF DAMAGE, AND ON ANY THEORY OF LIABILITY, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.

6 Feature Extraction Reference Guide

Feature Extraction Reference Guide 7

Content

1 Default Protocol Settings 13

Default Protocol Settingsan Introduction 14

Differences between CGH and gene expression microarrays 15 Hidden Settings 15

Tables of Default Protocol Settings 16

CGH_1201_Sep17 16 ChIP_1200_Jun14 24 GE1_1200_Jun14 31 GE2_1200_Dec17 37 GE2-NonAT_1100_Jul11 44 miRNA_1200_Jun14 49

Differences in Protocol Settings Based on Each Step 56

Place Grid 57 Optimize Grid fit 58 Find spots 59 Flag outliers 60 Compute Bkgd, Bias and Error 62 Correct Dye Biases 65 Compute ratios, calculate metrics, and generate results 66

2 QC Report Results 67

QC Reports 68

2-color Gene Expression QC Report 69 1-color Gene Expression QC Report 72 Streamlined CGH QC Report 75 CGH_ChIP QC Report 77 MicroRNA (miRNA) QC Report 79 Non-Agilent GE2 QC Report 81 QC reports with metric sets added 83

8 Feature Extraction Reference Guide

Contents

QC Report Headers 87

2-color Gene Expression QC Report 87 1-color Gene Expression QC Report 88 Streamlined CGH QC Report 88 CGH_ChIP QC Report 88 MicroRNA (miRNA) QC Report 89 Non-Agilent 2-color gene expression QC Report 89

Feature Statistics 90

Spot finding of Four Corners 90 Outlier Stats 91 Spatial Distribution of All Outliers 91 Net Signal Statistics 93 Negative Control Stats 94 Plot of Background-Corrected Signals 95 Histogram of Signals Plot (1-color GE or CGH) 96 Local Background Inliers 97 Foreground Surface Fit 97 Multiplicative Surface Fit 99 Spatial Distribution of Significantly Up-Regulated and Down-Regulated

Features (Positive and Negative Log Ratios) 100 Plot of LogRatio vs. Log ProcessedSignal 101 Spatial Distribution of Median Signals for each Row and Column 102 Histogram of LogRatio plot 103

Inter-Feature Statistics 104

Reproducibility Statistics (%CV Replicated Probes) 104 Microarray Uniformity (2-color only) 106 Sensitivity 107 Reproducibility Plots 108 Spike-in Signal Statistics 111 Spike-in Linearity Check for 2-color Gene Expression 113 Spike-in Linearity Check for 1-color Gene Expression 114

QC Report Results in the FEPARAMS and Stats Tables 121

Contents

Feature Extraction Reference Guide 9

QC Metric Set Results 122

CGH_QCMT_Sep17 122 ChIP_QCMT_Jun14 123 GE1_QCMT_Jun14 123 GE2_QCMT_Dec17 124 miRNA_QCMT_Jun14 124 Metric Evaluation Logic 125

3 Text File Parameters and Results 127

Parameters/options (FEPARAMS) 129

FULL FEPARAMS Table 129 COMPACT FEPARAMS Table 151 QC FEPARAMS Table 154 MINIMAL FEPARAMS Table 157

Statistical results (STATS) 160

STATS Table (ALL text output types) 160

Feature results (FEATURES) 179

FULL Features Table 179 COMPACT Features Table 190 QC Features Table 195 MINIMAL Features Table 201 Other text result file annotations 205

4 MAGE-ML (XML) File Results 207

How Agilent output file formats are used by databases 208

MAGE-ML results 209

Differences between MAGE-ML and text result files 209 Full and Compact Output Packages 209 Tables for Full Output Package 210 Table for Compact Output Package 218

Helpful hints for transferring Agilent output files 222

10 Feature Extraction Reference Guide

Contents

XML output 222 TIFF Results 224

5 How Algorithms Calculate Results 225

Overview of Feature Extraction algorithms 226

Algorithms and functions they perform 226 Algorithms and results they produce 232

XDR Extraction Process 236

What is XDR scanning? 236 XDR Feature Extraction process 236 How the XDR algorithm works 238 Troubleshooting the XDR extraction 239

How each algorithm calculates a result 240

Place Grid 240 Optimize Grid Fit 243 Find Spots 243 Flag Outliers 250 Compute Bkgd, Bias and Error 256 Correct Dye Biases 276 Compute Ratios 280 Calculate Metrics 282 MicroRNA Analysis 285

Example calculations for feature 12519 of Agilent Human 22K image 292

Data from the FEPARAMS table 293 Data from the STATS Table 293 Data from the FEATURES Table 293

6 Command Line Feature Extraction 299

Commands 301

Command line syntax 301 Commands and arguments 302

Contents

Feature Extraction Reference Guide 11

Return Codes 307

Extraction Input 309

Extraction Results 314

Status information 314 Examples of status information 315 Error codes from XML file 317 Warning codes from XML file 321

Index 327

12 Feature Extraction Reference Guide

Contents

13Agilent Technologies

Agilent Feature Extraction 12.2 Reference Guide

1 Default Protocol Settings

Default Protocol Settingsan Introduction 14

Tables of Default Protocol Settings 16

Differences in Protocol Settings Based on Each Step 56

See the Feature Extraction 12.2 User Guide to learn the purpose of all the parameters and settings and how to modify them.

When a protocol is assigned to an extraction set, the software loads a set of protocol parameter values and settings that affect the process and results for Feature Extraction.

Agilent protocols are meant for use with Agilent microarrays scanned with an Agilent scanner. They are intended for use with arrays that use Agilent default lab procedures (label, hybridization, wash, and scanning methods). The non-Agilent protocol is meant for use with non-Agilent microarrays that are scanned with an Agilent scanner.

Parameter values in the protocol depend on the microarray type and your experiment. The following pages list the default settings for each of the protocol templates shipped or downloaded with the software. Each protocol template represents a different microarray type. You can display these settings and values when you open the Protocol Editor for each of the protocol templates.

14 Feature Extraction Reference Guide

1 Default Protocol Settings Default Protocol Settingsan Introduction

Default Protocol Settingsan Introduction

To learn more about changing the default values for the protocols, see the Feature Extraction 12.2 User Guide.

This chapter presents tables for display of the default settings for each protocol. Parameter values depend on:

microarray type

lab protocol

formats

scanner used

To learn about the naming of the protocol templates, see the Feature Extraction 12.2 User Guide. Agilent provides new and updated protocols on the eArray website. If you set up an eArray login in Feature Extraction, the software can automatically download and install protocol updates from eArray. See the Feature Extraction 12.2 User Guide for more details.

Listed in the following table are the names of the nonremovable protocols and where you can find the tables that list their default values.

Table 1 Location of protocol template default settings

Protocol Template name Location in chapter

CGH_1201_Sep17 page 16

ChIP_1200_Jun14 page 24

GE1_1200_Jun14 page 31

GE2_1200_Dec17 page 37

GE2-NonAT_1100_Jul11 page 44

miRNA_1200_Jun14 page 49

Default Protocol Settings 1 Differences between CGH and gene expression microarrays

Feature Extraction Reference Guide 15

Differences between CGH and gene expression microarrays

To see the differences in some default settings between protocols, go to GE2_1200_Dec17 on page 37.

CGH microarrays possess a different negative control sequence scheme than the gene expression microarrays. The gene expression microarrays have many replicate negative control features using only one sequence. The CGH microarrays have many sequences of negative controls that span the range of sequence variability seen in the biological probes used on the microarrays. This difference in the control grid (especially the multiple sequences used for negative controls) leads to a difference in protocol settings.

Hidden Settings

To create a protocol for a specific type of microarray, you are required to use an Agilent- created protocol or user- created protocol for the same type of microarray.

The Tables of Default Protocol Settings show only the default visible parameter values for the steps of the protocol. You can see the hidden parameters in the FE PARAMS table. See Parameters/options (FEPARAMS) on page 129. Many of these hidden parameters are image- processing ones that are chosen using the Automatically Determine function.

CAUTION Protocol templates provide both visible and hidden settings whose values are specific to the type or format of microarrays. Although you can change the visible settings so that any two protocols of different type appear identical, you cannot change the hidden settings that distinguish these protocols from one another.

16 Feature Extraction Reference Guide

1 Default Protocol Settings Tables of Default Protocol Settings

Tables of Default Protocol Settings

CGH_1201_Sep17

This protocol is a CGH protocol for use with the Oligonucleotide Array- Based CGH for Genomic DNA Analysis (Enzymatic User Manual version 6.1 or higher, ULS User Manual version 3.1 or higher).

CAUTION These protocol settings may not be optimum for non-Agilent microarrays or Agilent microarrays processed with non-Agilent procedures. You determine the settings and values that are optimum for your system.

Table 2 Default settings for CGH_1201_Sep17 protocol

Protocol step Parameter Default Setting/Value (v12.2)

Place Grid Array Format For any format automatically determined or selected by you, the software uses the default Placement Method.

Parameters that apply to specific formats appear only if that format is selected.

Automatically Determine

[Recognized formats: Single Density (11k, 22k), 25k, Double Density (44k), 95k, 185k, 185k 10 uM, 65-micron feature size (also with 10-micron scans), 30-micron feature size single pack and multi pack, and Third Party]

Placement Method Hidden if Array Format is set to Automatically Determine.

Allow Some Distortion (All formats)

Enable Background Peak Shifting Hidden if Array Format is set to Automatically Determine.

Set to False for all arrays except 30 microns single pack and multi pack, for which it is set to True.

Default Protocol Settings 1 CGH_1201_Sep17

Feature Extraction Reference Guide 17

Use central part of pack for slope and skew calculation?

Hidden if Array Format is set to Automatically Determine.

Set to False for all arrays except 30 microns single pack and multi pack, for which it is set to True.

Use the correlation method to obtain origin X of subgrids

Hidden if Array Format is set to Automatically Determine.

Set to False for all arrays except 30 microns single pack and multi pack, for which it is set to True.

Use Enhanced Gridding

Apply the enhanced gridding feature released in Feature Extraction 12.1. The enhancements include a new iterative method for determining grid position, rotation, and skew, and several fine grid tuning methods that improve the calculation of rotation and skew. Enhanced gridding also uses both the foreground and background of the corner stencil patterns to improve identification of grid corners.

True

Note: Results obtained with protocols that use enhanced gridding may vary slightly from results obtained with previous gridding algorithms (e.g., fewer gridding errors). Use appropriate validation processes when switching from previous CGH protocols to ones that use enhanced gridding.

Optimize Grid Fit Grid Format The parameters and values for optimizing the grid differ depending on the format.

Automatically Determine

[Recognized formats: 65-micron feature size, 30-micron feature size, and Third Party]

Iteratively Adjust Corners? Hidden if Array Format is set to Automatically Determine.

True (All Formats, except Third Party)

False (Third Party)

Adjustment Threshold Hidden if Array Format is set to Automatically Determine.

0.300 (All Formats, except Third Party)

Table 2 Default settings for CGH_1201_Sep17 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

18 Feature Extraction Reference Guide

1 Default Protocol Settings CGH_1201_Sep17

Maximum Number of Iterations Hidden if Array Format is set to Automatically Determine.

5 (All Formats, except Third Party)

Found Spot Threshold Hidden if Array Format is set to Automatically Determine.

0.200 (All Formats, except Third Party)

Number of Corner Feature Side Dimension?

Hidden if Array Format is set to Automatically Determine.

20 (All Formats, except Third Party)

Find Spots Spot Format Depending on the format selected by the software or by you, the default settings for this step change. See the following rows for the default values for finding spots.

Automatically Determine

[Recognized formats: Single Density (11k, 22k), 25k, Double Density (44k), 95k, 185k, 185k 10 uM, 244k 10uM, 65-micron feature size, 30-micron feature size, and Third Party]

Use the Nominal Diameter from the Grid Template

Hidden if Array Format is set to Automatically Determine.

True (All Formats)

Spot Deviation Limit Hidden if Array Format is set to Automatically Determine.

8.0 for all formats except for third party, for which it is set to 1.5

Calculation of Spot Statistics Method

Hidden if Array Format is set to Automatically Determine.

Use Cookie (All Formats)

Cookie Percentage Hidden if Array Format is set to Automatically Determine.

0.650 (Single Density, 25k)

0.561 (Double Density, 95k)

0.700 (185k, 185k 10 uM, 244k 10 uM, 65-micron feature size)

Table 2 Default settings for CGH_1201_Sep17 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

Default Protocol Settings 1 CGH_1201_Sep17

Feature Extraction Reference Guide 19

0.750 (30-micron feature size)

Exclusion Zone Percentage Hidden if Array Format is set to Automatically Determine.

1.200 (All Formats except 30-micron feature size)

1.300 (30-micron feature size)

Auto Estimate the Local Radius Hidden if Array Format is set to Automatically Determine.

True (Single Density, Double Density, 25k, 95k)

False (185k, 185k 10uM, 65-micron feature size, 30-micron feature size, 244k 10uM)

LocalBGRadius Hidden if Array Format is set to Automatically Determine.

100 (when False for 185k, 185k 10uM, 65-micron feature size, 244k 10 uM)

150 (when False for 30-micron feature size)

Pixel Outlier Rejection Method Inter Quartile Region (Automatically Determine and All Formats)

RejectIQRFeat 1.42 (All Formats)

RejectIQRBG 1.42 (All Formats)

Statistical Method for Spot Values from Pixels Use Mean/Standard Deviation (Automatically Determine and All Formats)

Table 2 Default settings for CGH_1201_Sep17 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

20 Feature Extraction Reference Guide

1 Default Protocol Settings CGH_1201_Sep17

Use Enhanced SpotFinding

This enhancement allows for more accurate placement of the center of each spot by increasing the area around the expected spot center in which the algorithm looks for pixels in the image that are attributable to that spot. If the increased search area captures pixels from neighboring spots, then the algorithm does not attribute those pixels to the spot.

False

Note: Results obtained with protocols that use enhanced spot finding may vary slightly from results obtained without spot finding (e.g., fewer non-uniform features). Use appropriate validation processes when switching to CGH protocols that use enhanced spot finding.

Flag Outliers Compute Population Outliers True

Minimum Population 10

IQRatio 1.42

Background IQRatio 1.42

Use Qtest for Small Populations? True

Report Population Outliers as Failed in MAGEML file

False

Compute Non Uniform Outliers True

Scanner The values for the parameters change depending on the scanner used for the image. See the following for differences.

Automatically Determine

Agilent scanner

Automatically Compute OL Polynomial Terms Hidden if Array Format is set to Automatically Determine.

True

Feature (%CV)^2 0.04000

Red Poissonian Noise Term Multiplier

5

Table 2 Default settings for CGH_1201_Sep17 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

Default Protocol Settings 1 CGH_1201_Sep17

Feature Extraction Reference Guide 21

Red Signal Constant Term Multiplier

1

Green Poissonian Noise Term Multiplier

5

Green Signal Constant Term Multiplier

1

Background (%CV)^2 0.09000

Red Poissonian Noise Term Multiplier

3

Red Background Constant Term Multiplier

1

Green Poissonian Noise Term Multiplier

3

Green Background Constant Term Multiplier

1

Compute Bkgd, Bias and Error

Background Subtraction Method No Background Subtraction

Significance (for IsPosAndSignif and IsWellAboveBG) Use Error Model for Significance

2-sided t-test of feature vs. background max p-value

0.01

WellAboveMulti 13

Signal CorrectionCalculate Surface Fit (required for Spatial Detrend)

True

Feature Set for Surface Fit OnlyNegativeControlFeatures

Perform Filtering for Surface Fit False

Perform Spatial Detrending True

Signal CorrectionAdjust Background Globally False

Signal CorrectionPerform Multiplicative Detrending True

Detrend on Replicates Only False

Table 2 Default settings for CGH_1201_Sep17 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

22 Feature Extraction Reference Guide

1 Default Protocol Settings CGH_1201_Sep17

Filter Low signal probes from Fit? True

Neg. Ctrl. Threshold Mult. Detrend Factor

3

Perform Filtering for Fit Use Window Average

Use polynomial data fit instead of LOESS?

True

Polynomial Multiplicative DetrendDegree

4

Robust Neg Ctrl Stats? True

Choose universal error, or most conservative Most Conservative

MultErrorGreen 0.1000

MultErrorRed 0.1000

Auto Estimate Add Error Red True

Auto Estimate Add Error Green True

Use Surrogates True

Correct Dye Biases Use Dye Norm List Automatically Determine

Dye Normalization Probe Selection Method Use Rank Consistent Probes

Rank Tolerance 0.050

Variable Rank Tolerance False

Omit Background Population Outliers False

Allow Positive and Negative Controls False

Signal Characteristics OnlyPositiveAndSignificantSignals

Normalization Correction Method Linear

Max Number Ranked Probes -1

Compute Ratios Peg Log Ratio Value 4.00

Table 2 Default settings for CGH_1201_Sep17 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

Default Protocol Settings 1 CGH_1201_Sep17

Feature Extraction Reference Guide 23

Calculate Metrics Spikein Target Used False

Min Population for Replicate Stats? 3

Grid Test Format Automatically Determine

Recognized formats: 60 micron and 30 micron feature size, third party

PValue for Differential Expression 0.010000

Percentile Value 75.00

Generate Results Type of QC Report Streamlined CGH

Generate Single Text File True

JPEG Down Sample Factor 4

Table 2 Default settings for CGH_1201_Sep17 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

24 Feature Extraction Reference Guide

1 Default Protocol Settings ChIP_1200_Jun14

ChIP_1200_Jun14

This protocol is a ChIP protocol for use with Agilent Mammalian ChIP- on- Chip and DNA methylation applications.

Table 3 Default settings for ChIP_1200_Jun14 protocol

Protocol step Parameter Default Setting/Value (v12.2)

Place Grid Array Format For any format automatically determined or selected by you, the software uses the default Placement Method.

Parameters that apply to specific formats appear only if that format is selected.

Automatically Determine

[Recognized formats: Single Density (11k, 22k), 25k, Double Density (44k), 95k, 185k, 185k 10 uM, 65-micron feature size (also with 10-micron scans), 30-micron feature size (single pack and multi pack) and Third Party]

Placement Method Hidden if Array Format is set to Automatically Determine.

Allow Some Distortion (All formats)

Enable Background Peak Shifting Hidden if Array Format is set to Automatically Determine.

Set to false for all arrays except 30 microns (single pack and multi pack), for which it is set to true.

Use central part of pack for slope and skew calculation?

Hidden if Array Format is set to Automatically Determine.

Set to False for all arrays except 30 microns single pack and multi pack, for which it is set to True.

Use the correlation method to obtain origin X of subgrids

Hidden if Array Format is set to Automatically Determine.

Set to False for all arrays except 30 microns single pack and multi pack, for which it is set to True.

Default Protocol Settings 1 ChIP_1200_Jun14

Feature Extraction Reference Guide 25

Use Enhanced Gridding

An enhanced automatic gridding algorithm was released in Feature Extraction 12.1 for use in CGH protocols only. Agilent has not validated the new algorithm in ChIP protocols.

False

Optimize Grid Fit Grid Format The parameters and values for optimizing the grid differ depending on the format.

Automatically Determine

[Recognized formats: 65-micron feature size, 30-micron feature size, and Third Party]

Iteratively Adjust Corners? Hidden if Array Format is set to Automatically Determine.

True (All Formats, except Third Party)

False (Third Party)

Adjustment Threshold Hidden if Array Format is set to Automatically Determine.

0.300(All Formats, except Third Party)

Maximum Number of Iterations Hidden if Array Format is set to Automatically Determine.

5 (All Formats, except Third Party)

Found Spot Threshold Hidden if Array Format is set to Automatically Determine.

0.200 (All Formats, except Third Party)

Number of Corner Feature Side Dimension?

Hidden if Array Format is set to Automatically Determine.

20 (All Formats, except Third Party)

Find Spots Spot Format Depending on the format selected by the software or by you, the default settings for this step change. See the following rows for the default values for finding spots.

Automatically Determine

[Recognized formats: same as those listed above except 244k 10uM replaces 65-micron feature size 10-micron scans]

Table 3 Default settings for ChIP_1200_Jun14 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

26 Feature Extraction Reference Guide

1 Default Protocol Settings ChIP_1200_Jun14

Use the Nominal Diameter from the Grid Template

Hidden if Array Format is set to Automatically Determine.

True (All Formats)

Spot Deviation Limit Hidden if Array Format is set to Automatically Determine.

8.0 for all formats except for third party, for which it is set to 1.5

Calculation of Spot Statistics Method

Hidden if Array Format is set to Automatically Determine.

Use Cookie (All Formats)

Cookie Percentage Hidden if Array Format is set to Automatically Determine.

0.650 (Single Density, 25k)

0.561 (Double Density, 95k)

0.700 (185k, 185k 10 uM, 244k 10 uM, 65-micron feature size)

0.750 (30-micron feature size)

Exclusion Zone Percentage Hidden if Array Format is set to Automatically Determine.

1.200 (All Formats except 30-micron feature size)

1.300 (30-micron feature size)

Auto Estimate the Local Radius Hidden if Array Format is set to Automatically Determine.

True (Single Density, Double Density, 25k, 95k)

False (185k, 185k 10uM, 65-micron feature size, 30-micron feature size, 244k 10uM)

Table 3 Default settings for ChIP_1200_Jun14 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

Default Protocol Settings 1 ChIP_1200_Jun14

Feature Extraction Reference Guide 27

LocalBGRadius Hidden if Array Format is set to Automatically Determine.

100 (when False for 185k, 185k 10uM, 65-micron feature size, 244k 10 uM)

150 (when False for 30-micron feature size)

Pixel Outlier Rejection Method Inter Quartile Region (Automatically Determine and All Formats)

RejectIQRFeat 1.42 (All Formats)

RejectIQRBG 1.42 (All Formats)

Statistical Method for Spot Values from Pixels Use Mean/Standard Deviation (Automatically Determine and All Formats)

Flag Outliers Compute Population Outliers True

Minimum Population 8

IQRatio 1.42

Background IQRatio 1.42

Use Qtest for Small Populations? True

Report Population Outliers as Failed in MAGEML file

False

Compute Non Uniform Outliers True

Scanner The values for the parameters change depending on the scanner used for the image. See the following for differences.

Automatically Determine

Agilent scanner

Automatically Compute OL Polynomial Terms Hidden if Array Format is set to Automatically Determine.

True

Table 3 Default settings for ChIP_1200_Jun14 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

28 Feature Extraction Reference Guide

1 Default Protocol Settings ChIP_1200_Jun14

Feature (%CV)^2 0.04000

Red Poissonian Noise Term Multiplier

5

Red Signal Constant Term Multiplier

1

Green Poissonian Noise Term Multiplier

5

Green Signal Constant Term Multiplier

1

Background (%CV)^2 0.09000

Red Poissonian Noise Term Multiplier

3

Red Background Constant Term Multiplier

1

Green Poissonian Noise Term Multiplier

3

Green Background Constant Term Multiplier

1

Compute Bkgd, Bias and Error

Background Subtraction Method No Background Subtraction

Significance (for IsPosAndSignif and IsWellAboveBG) Use Error Model for Significance

2-sided t-test of feature vs. background max p-value

0.01

WellAboveMulti 13

Signal CorrectionCalculate Surface Fit (required for Spatial Detrend)

True

Feature Set for Surface Fit OnlyNegativeControlFeatures

Perform Filtering for Surface Fit False

Perform Spatial Detrending True

Table 3 Default settings for ChIP_1200_Jun14 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

Default Protocol Settings 1 ChIP_1200_Jun14

Feature Extraction Reference Guide 29

Signal CorrectionAdjust Background Globally False

Signal CorrectionPerform Multiplicative Detrending True

Detrend on Replicates Only False

Filter Low signal probes from Fit? True

Neg. Ctrl. Threshold Mult. Detrend Factor

3

Perform Filtering for Fit Use Window Average

Use polynomial data fit instead of LOESS?

True

Polynomial Multiplicative DetrendDegree

4

Robust Neg Ctrl Stats? True

Choose universal error, or most conservative Most Conservative

MultErrorGreen 0.1000

MultErrorRed 0.1000

Auto Estimate Add Error Red True

Auto Estimate Add Error Green True

Use Surrogates True

Correct Dye Biases Use Dye Norm List Automatically Determine

Dye Normalization Probe Selection Method Use Rank Consistent Probes

Rank Tolerance 0.050

Variable Rank Tolerance False

Omit Background Population Outliers False

Allow Positive and Negative Controls False

Signal Characteristics OnlyPositiveAndSignificantSignals

Table 3 Default settings for ChIP_1200_Jun14 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

30 Feature Extraction Reference Guide

1 Default Protocol Settings ChIP_1200_Jun14

Normalization Correction Method Linear

Max Number Ranked Probes -1

Compute Ratios Peg Log Ratio Value 4.00

Calculate Metrics Spikein Target Used False

Min Population for Replicate Stats? 3

Grid Test Format Automatically Determine

Recognized formats: 60 micron and 30 micron feature size, third party

PValue for Differential Expression 0.010000

Percentile Value 75.00

Generate Results Type of QC Report CGH_ChIP

Generate Single Text File True

JPEG Down Sample Factor 4

Table 3 Default settings for ChIP_1200_Jun14 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

Default Protocol Settings 1 GE1_1200_Jun14

Feature Extraction Reference Guide 31

GE1_1200_Jun14

This protocol is a 1- color gene expression protocol for use with the One- Color Microarray- Based Gene Expression Analysis (Quick Amp Labeling) (lab protocol v5.7 or higher, publication number G4140- 90040 or G4140- 90041 for Tecan HS Pro Hybridization).

Table 4 Default settings for GE1_1200_Jun14 protocol

Protocol step Parameter Default Setting/Value (v12.2)

Place Grid Array Format For any format automatically determined or selected by you, the software uses the default Placement Method.

Parameters that apply to specific formats appear only if that format is selected.

Automatically Determine

[Recognized formats: Single Density (11k, 22k), 25k, Double Density (44k), 95k, 185k, 185k 10 uM, 65-micron feature size (also with 10-micron scans), 30-micron feature size (single pack and multi pack) and Third Party]

Placement Method Hidden if Array Format is set to Automatically Determine.

Allow Some Distortion (All formats)

Enable Background Peak Shifting Hidden if Array Format is set to Automatically Determine.

Set to false for all arrays except 30 microns (single pack and multi pack), for which it is set to true.

Use central part of pack for slope and skew calculation?

Hidden if Array Format is set to Automatically Determine.

Set to False for all arrays except 30 microns single pack and multi pack, for which it is set to True.

Use the correlation method to obtain origin X of subgrids

Hidden if Array Format is set to Automatically Determine.

Set to False for all arrays except 30 microns single pack and multi pack, for which it is set to True.

32 Feature Extraction Reference Guide

1 Default Protocol Settings GE1_1200_Jun14

Use Enhanced Gridding

An enhanced automatic gridding algorithm was released in Feature Extraction 12.1 for use in CGH protocols only. Agilent has not validated the new algorithm in GE1 protocols.

False

Optimize Grid Fit Grid Format The parameters and values for optimizing the grid differ depending on the format,

Automatically Determine

[Recognized formats: 65-micron feature size, 30-micron feature size, and Third Party]

Iteratively Adjust Corners? Hidden if Array Format is set to Automatically Determine.

True (All Formats, except Third Party)

False (Third Party)

Adjustment Threshold Hidden if Array Format is set to Automatically Determine.

0.300(All Formats, except Third Party)

Maximum Number of Iterations Hidden if Array Format is set to Automatically Determine.

5 (All Formats, except Third Party)

Found Spot Threshold Hidden if Array Format is set to Automatically Determine.

0.200 (All Formats, except Third Party)

Number of Corner Feature Side Dimension?

Hidden if Array Format is set to Automatically Determine.

20 (All Formats, except Third Party)

Find Spots Spot Format Depending on the format selected by the software or by you, the default settings for this step change. See the following rows for the default values for finding spots.

Automatically Determine

[Recognized formats: same as those listed above except 244k 10uM replaces 65-micron feature size 10-micron scans]

Table 4 Default settings for GE1_1200_Jun14 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

Default Protocol Settings 1 GE1_1200_Jun14

Feature Extraction Reference Guide 33

Use the Nominal Diameter from the Grid Template

Hidden if Array Format is set to Automatically Determine.

True (All Formats)

Spot Deviation Limit Hidden if Array Format is set to Automatically Determine.

8.0 for all formats except for third party, for which it is set to 1.5

Calculation of Spot Statistics Method

Hidden if Array Format is set to Automatically Determine.

Use Cookie (All Formats)

Cookie Percentage Hidden if Array Format is set to Automatically Determine.

0.650 (Single Density, 25k)

0.561 (Double Density, 95k)

0.700 (185k, 185k 10 uM, 244k 10 uM, 65-micron feature size)

0.750 (30-micron feature size)

Exclusion Zone Percentage Hidden if Array Format is set to Automatically Determine.

1.200 (All Formats except 30-micron feature size)

1.300 (30-micron feature size)

Auto Estimate the Local Radius Hidden if Array Format is set to Automatically Determine.

True (Single Density, Double Density, 25k, 95k)

False (185k, 185k 10uM, 65-micron feature size, 30-micron feature size, 244k 10uM)

Table 4 Default settings for GE1_1200_Jun14 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

34 Feature Extraction Reference Guide

1 Default Protocol Settings GE1_1200_Jun14

LocalBGRadius Hidden if Array Format is set to Automatically Determine.

100 (when False for 185k, 185k 10uM, 65-micron feature size, 244k 10 uM)

150 (when False for 30-micron feature size)

Pixel Outlier Rejection Method Inter Quartile Region (Automatically Determine and All Formats)

RejectIQRFeat 1.42 (All Formats)

RejectIQRBG 1.42 (All Formats)

Statistical Method for Spot Values from Pixels Use Mean/Standard Deviation (Automatically Determine and All Formats)

Flag Outliers Compute Population Outliers True

Minimum Population 10

IQRatio 1.42

Background IQRatio 1.42

Use Qtest for Small Populations? True

Report Population Outliers as Failed in MAGEML file

False

Compute Non Uniform Outliers True

Scanner The values for the parameters change depending on the scanner used for the image. See the following for differences.

Automatically Determine

Agilent scanner

Automatically Compute OL Polynomial Terms Hidden if Array Format is set to Automatically Determine.

True

Table 4 Default settings for GE1_1200_Jun14 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

Default Protocol Settings 1 GE1_1200_Jun14

Feature Extraction Reference Guide 35

Feature (%CV)^2 0.04000

Green Poissonian Noise Term Multiplier

20

Green Signal Constant Term Multiplier

1

Background (%CV)^2 0.09000

Green Poissonian Noise Term Multiplier

3

Green Background Constant Term Multiplier

1

Compute Bkgd, Bias and Error

Background Subtraction Method No Background Subtraction

Significance (for IsPosAndSignif and IsWellAboveBG) Use Error Model for Significance

2-sided t-test of feature vs. background max p-value

0.01

WellAboveMulti 13

Signal CorrectionCalculate Surface Fit (required for Spatial Detrend)

True

Feature Set for Surface Fit FeaturesInNegativeControlRange

Perform Filtering for Surface Fit True

Perform Spatial Detrending True

Signal CorrectionAdjust Background Globally False

Signal CorrectionPerform Multiplicative Detrending True

Detrend on Replicates Only True

Filter Low signal probes from Fit? True

Neg. Ctrl. Threshold Mult. Detrend Factor

5

Perform Filtering for Fit Use Window Average

Table 4 Default settings for GE1_1200_Jun14 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

36 Feature Extraction Reference Guide

1 Default Protocol Settings GE1_1200_Jun14

Use polynomial data fit instead of LOESS?

True

Polynomial Multiplicative DetrendDegree

4

Robust Neg Ctrl Stats? False

Choose universal error, or most conservative Most Conservative

MultErrorGreen 0.1000

Auto Estimate Add Error Green True

Use Surrogates True

Calculate Metrics Spikein Target Used True

Min Population for Replicate Stats? 5

Grid Test Format Automatically Determine

Recognized formats: 60 micron and 30 micron feature size, third party

PValue for Differential Expression 0.010000

Percentile Value 75.00

Generate Results Type of QC Report Gene Expression

Generate Single Text File True

JPEG Down Sample Factor 4

Table 4 Default settings for GE1_1200_Jun14 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

Default Protocol Settings 1 GE2_1200_Dec17

Feature Extraction Reference Guide 37

GE2_1200_Dec17

This is a 2- color gene expression protocol for use with the Two- color Microarray- Based Gene Expression Analysis (Quick Amp Labeling) (lab protocol v5.7 or higher, publication number G4140- 90050 or G4140- 90051 for Tecan HS Pro Hybridization).

Table 5 Default settings for GE2_1200_Dec17 protocol

Protocol step Parameter Default Setting/Value (v12.2)

Place Grid Array Format For any format automatically determined or selected by you, the software uses the default Placement Method.

Parameters that apply to specific formats appear only if that format is selected.

Automatically Determine

[Recognized formats: Single Density (11k, 22k), 25k, Double Density (44k), 95k, 185k, 185k 10 uM, 65-micron feature size (also with 10-micron scans), 30-micron feature size (single pack and multi pack) and Third Party]

Placement Method Hidden if Array Format is set to Automatically Determine.

Allow Some Distortion (All formats)

Enable Background Peak Shifting Hidden if Array Format is set to Automatically Determine.

Set to false for all arrays except 30 microns (single pack and multi pack), for which it is set to true.

Use central part of pack for slope and skew calculation?

Hidden if Array Format is set to Automatically Determine.

Set to False for all arrays except 30 microns single pack and multi pack, for which it is set to True.

Use the correlation method to obtain origin X of subgrids

Hidden if Array Format is set to Automatically Determine.

Set to False for all arrays except 30 microns single pack and multi pack, for which it is set to True.

38 Feature Extraction Reference Guide

1 Default Protocol Settings GE2_1200_Dec17

Use Enhanced Gridding

An enhanced automatic gridding algorithm was released in Feature Extraction 12.1 for use in CGH protocols only. Agilent has not validated the new algorithm in GE2 protocols.

False

Optimize Grid Fit Grid Format The parameters and values for optimizing the grid differ depending on the format.

Automatically Determine

[Recognized formats: 65-micron feature size, 30-micron feature size, and Third Party]

Iteratively Adjust Corners? Hidden if Array Format is set to Automatically Determine.

True (All Formats, except Third Party)

False (Third Party)

Adjustment Threshold Hidden if Array Format is set to Automatically Determine.

0.300 (All Formats, except Third Party)

Maximum Number of Iterations Hidden if Array Format is set to Automatically Determine.

5 (All Formats, except Third Party)

Found Spot Threshold Hidden if Array Format is set to Automatically Determine.

0.200 (All Formats, except Third Party)

Number of Corner Feature Side Dimension?

Hidden if Array Format is set to Automatically Determine.

20 (All Formats, except Third Party)

Find Spots Spot Format Depending on the format selected by the software or by you, the default settings for this step change. See the following rows for the default values for finding spots.

Automatically Determine

[Recognized formats: same as those listed above except 244k 10uM replaces 65-micron feature size 10-micron scans]

Table 5 Default settings for GE2_1200_Dec17 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

Default Protocol Settings 1 GE2_1200_Dec17

Feature Extraction Reference Guide 39

Use the Nominal Diameter from the Grid Template

Hidden if Array Format is set to Automatically Determine.

True (All Formats)

Spot Deviation Limit Hidden if Array Format is set to Automatically Determine.

8.0 for all formats except for third party, for which it is set to 1.5

Calculation of Spot Statistics Method

Hidden if Array Format is set to Automatically Determine.

Use Cookie (All Formats)

Cookie Percentage Hidden if Array Format is set to Automatically Determine.

0.650 (Single Density, 25k)

0.561 (Double Density, 95k)

0.700 (185k, 185k 10 uM, 244k 10 uM, 65-micron feature size)

0.750 (30-micron feature size)

Exclusion Zone Percentage Hidden if Array Format is set to Automatically Determine.

1.200 (All Formats except 30-micron feature size)

1.300 (30-micron feature size)

Auto Estimate the Local Radius Hidden if Array Format is set to Automatically Determine.

True (Single Density, Double Density, 25k, 95k)

False (185k, 185k 10uM, 65-micron feature size, 30-micron feature size, 244k 10uM)

Table 5 Default settings for GE2_1200_Dec17 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

40 Feature Extraction Reference Guide

1 Default Protocol Settings GE2_1200_Dec17

LocalBGRadius Hidden if Array Format is set to Automatically Determine.

100 (when False for 185k, 185k 10uM, 65-micron feature size, 244k 10 uM)

150 (when False for 30-micron feature size)

Pixel Outlier Rejection Method Inter Quartile Region (Automatically Determine and All Formats)

RejectIQRFeat 1.42 (All Formats)

RejectIQRBG 1.42 (All Formats)

Statistical Method for Spot Values from Pixels Use Mean/Standard Deviation (Automatically Determine and All Formats)

Flag Outliers Compute Population Outliers True

Minimum Population 10

IQRatio 1.42

Background IQRatio 1.42

Use Qtest for Small Populations? True

Report Population Outliers as Failed in MAGEML file

False

Compute Non Uniform Outliers True

Scanner The values for the parameters change depending on the scanner used for the image. See the following for differences.

Automatically Determine

Agilent scanner

Automatically Compute OL Polynomial Terms Hidden if Array Format is set to Automatically Determine.

True

Table 5 Default settings for GE2_1200_Dec17 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

Default Protocol Settings 1 GE2_1200_Dec17

Feature Extraction Reference Guide 41

Feature (%CV)^2 0.04

Red Poissonian Noise Term Multiplier

20

Red Signal Constant Term Multiplier

1

Green Poissonian Noise Term Multiplier

20

Green Signal Constant Term Multiplier

1

Background (%CV)^2 0.09000

Red Poissonian Noise Term Multiplier

3

Red Background Constant Term Multiplier

1

Green Poissonian Noise Term Multiplier

3

Green Background Constant Term Multiplier

1

Compute Bkgd, Bias and Error

Background Subtraction Method No Background Subtraction

Significance (for IsPosAndSignif and IsWellAboveBG) Use Error Model for Significance

2-sided t-test of feature vs. background max p-value

0.01

WellAboveMulti 13

Signal CorrectionCalculate Surface Fit (required for Spatial Detrend)

True

Feature Set for Surface Fit FeaturesInNegativeControlRange

Perform Filtering for Surface Fit True

Perform Spatial Detrending True

Table 5 Default settings for GE2_1200_Dec17 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

42 Feature Extraction Reference Guide

1 Default Protocol Settings GE2_1200_Dec17

Signal CorrectionAdjust Background Globally False

Signal CorrectionPerform Multiplicative Detrending True

Detrend on Replicates Only True

Filter Low signal probes from Fit? True

Neg. Ctrl. Threshold Mult. Detrend Factor

5

Perform Filtering for Fit Use Window Average

Robust Neg Ctrl Stats? False

Choose universal error, or most conservative Most Conservative

MultErrorGreen 0.1000

MultErrorRed 0.1000

Auto Estimate Add Error Red True

Auto Estimate Add Error Green True

Use Surrogates True

Correct Dye Biases Use Dye Norm List Automatically Determine

Dye Normalization Probe Selection Method Use Rank Consistent Probes

Rank Tolerance 0.050

Variable Rank Tolerance False

Omit Background Population Outliers False

Allow Positive and Negative Controls False

Signal Characteristics OnlyPositiveAndSignificantSignals

Normalization Correction Method Linear and Lowess

Max Number Ranked Probes 8000

Compute Ratios Peg Log Ratio Value 4.00

Calculate Metrics Spikein Target Used True

Table 5 Default settings for GE2_1200_Dec17 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

Default Protocol Settings 1 GE2_1200_Dec17

Feature Extraction Reference Guide 43

Min Population for Replicate Stats? 5

Grid Test Format Automatically Determine

Recognized formats: 60 micron and 30 micron feature size, third party

PValue for Differential Expression 0.010000

Percentile Value 75.00

Generate Results Type of QC Report Gene Expression

Generate Single Text File True

JPEG Down Sample Factor 4

Table 5 Default settings for GE2_1200_Dec17 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

44 Feature Extraction Reference Guide

1 Default Protocol Settings GE2-NonAT_1100_Jul11

GE2-NonAT_1100_Jul11

Use this protocol for running Feature Extraction on non- Agilent microarrays scanned with the Agilent scanner.

Table 6 Default settings for GE2-NonAT_1100_Jul11 protocol

Protocol step Parameter Default Setting/Value (v12.2)

Place Grid Array Format For any format automatically determined or selected by you, the software uses the default Placement Method.

Parameters that apply to specific formats appear only if that format is selected.

Automatically Determine

[Recognized formats: Single Density (11k, 22k), 25k, Double Density (44k), 95k, 185k, 185k 10 uM, 65-micron feature size (also with 10-micron scans), 30-micron feature size (single pack and multi pack) and Third Party]

Placement Method Hidden if Array Format is set to Automatically Determine.

Allow Some Distortion

Enable Background Peak Shifting Hidden if Array Format is set to Automatically Determine.

Set to false for all arrays except 30 microns (single pack and multi pack), for which it is set to true.

Use central part of pack for slope and skew calculation?

Hidden if Array Format is set to Automatically Determine.

Set to False for all arrays except 30 microns single pack and multi pack, for which it is set to True.

Use the correlation method to obtain origin X of subgrids

Hidden if Array Format is set to Automatically Determine.

Set to False for all arrays except 30 microns single pack and multi pack, for which it is set to True.

Default Protocol Settings 1 GE2-NonAT_1100_Jul11

Feature Extraction Reference Guide 45

Use Enhanced Gridding

An enhanced automatic gridding algorithm was released in Feature Extraction 12.1 for use in CGH protocols only. Agilent has not validated the new algorithm in GE2 protocols.

False

Optimize Grid Fit Grid Format The parameters and values for optimizing the grid differ depending on the format.

Automatically Determine

[Recognized formats: 65-micron feature size, 30-micron feature size, and Third Party]

Iteratively Adjust Corners? Hidden if Array Format is set to Automatically Determine.

True (All Formats, except Third Party)

False (Third Party)

Adjustment Threshold Hidden if Array Format is set to Automatically Determine.

0.300 (All Formats, except Third Party)

Maximum Number of Iterations Hidden if Array Format is set to Automatically Determine.

5 (All Formats, except Third Party)

Found Spot Threshold Hidden if Array Format is set to Automatically Determine.

0.200 (All Formats, except Third Party)

Number of Corner Feature Side Dimension?

Hidden if Array Format is set to Automatically Determine.

20 (All Formats, except Third Party)

Find Spots Spot Format Third Party

Use the Nominal Diameter from the Grid Template

True

Spot Deviation Limit 1.50

Table 6 Default settings for GE2-NonAT_1100_Jul11 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

46 Feature Extraction Reference Guide

1 Default Protocol Settings GE2-NonAT_1100_Jul11

Calculation of Spot Statistics Method

Use Cookie

Cookie Percentage 1.000

Exclusion Zone Percentage 1.200

Auto Estimate the Local Radius True

LocalBGRadius 127, if False

Pixel Outlier Rejection Method Inter Quartile Region

RejectIQRFeat 1.42

RejectIQRBG 1.42

Statistical Method for Spot Values from Pixels Use Mean/Standard Deviation

Flag Outliers Compute Population Outliers True

Minimum Population 15

IQRatio 1.42

Background IQRatio 1.42

Use Qtest for Small Populations? True

Report Population Outliers as Failed in MAGEML file

False

Compute Non Uniform Outliers True

Automatically Compute OL Polynomial Terms False

Feature (%CV)^2 0.11000

Poissonian Noise Term 320

Background Term 600

Background (%CV)^2 0.09000

Poissonian Noise Term 320

Background Term 600

Table 6 Default settings for GE2-NonAT_1100_Jul11 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

Default Protocol Settings 1 GE2-NonAT_1100_Jul11

Feature Extraction Reference Guide 47

Compute Bkgd, Bias and Error

Background Subtraction Method Local Background

Significance (for IsPosAndSignif and IsWellAboveBG) Use Pixel Statistics for Significance

2-sided t-test of feature vs. background max p-value

0.01

WellAboveMulti 2.6

Signal CorrectionCalculate Surface Fit (required for Spatial Detrend)

True

Feature Set for Surface Fit AllFeatureTypes

Perform Filtering for Surface Fit True

Perform Spatial Detrending False

Signal CorrectionAdjust Background Globally True

Adjust Background Globally to: 0

Robust Neg Ctrl Stats? False

Choose universal error, or most conservative Most Conservative

MultErrorGreen 0.0900

MultErrorRed 0.0900

Auto Estimate Add Error Red False

Additive Error Value Red 30

Auto Estimate Add Error Green False

Additive Error Value Green 30

Use Surrogates True

Correct Dye Biases Use Dye Norm List Automatically Determine

Dye Normalization Probe Selection Method Use Rank Consistent Probes

Rank Tolerance 0.050

Variable Rank Tolerance False

Table 6 Default settings for GE2-NonAT_1100_Jul11 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

48 Feature Extraction Reference Guide

1 Default Protocol Settings GE2-NonAT_1100_Jul11

Omit Background Population Outliers False

Allow Positive and Negative Controls False

Signal Characteristics OnlyPositiveAndSignificantSignals

Normalization Correction Method Lowess Only

Max Number Ranked Probes 8000

Compute Ratios Peg Log Ratio Value 4.00

Calculate Metrics Spikein Target Used False

Min Population for Replicate Stats? 5

PValue for Differential Expression 0.010000

Percentile Value 75.00

Generate Results Generate Single Text File True

JPEG Down Sample Factor 4

Table 6 Default settings for GE2-NonAT_1100_Jul11 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

Default Protocol Settings 1 miRNA_1200_Jun14

Feature Extraction Reference Guide 49

miRNA_1200_Jun14

This protocol is a miRNA protocol for use with miRNA Microarray System with miRNA Complete Labeling and Hyb Kit (lab protocol v2.0 or higher, publication number G4170- 90011).

Table 7 Default settings for miRNA_1200_Jun14 protocol

Protocol step Parameter Default Setting/Value (v12.2)

Place Grid Array Format For any format automatically determined or selected by you, the software uses the default Placement Method.

Parameters that apply only to specific formats appear only if that format is selected.

Automatically Determine

[Recognized formats: Single Density (11k, 22k), 25k, Double Density (44k), 95k, 185k, 185k 10 uM, 65-micron feature size (also with 10-micron scans), 30-micron feature size (single pack and multi pack) and Third Party]

Placement Method Hidden if Array Format is set to Automatically Determine.

Allow Some Distortion (All formats)

Enable Background Peak Shifting Hidden if Array Format is set to Automatically Determine.

Set to false for all arrays except 30 microns (single pack and multi pack), for which it is set to true.

Use central part of pack for slope and skew calculation?

Hidden if Array Format is set to Automatically Determine.

Set to False for all arrays except 30 microns single pack and multi pack, for which it is set to True.

Use the correlation method to obtain origin X of subgrids

Hidden if Array Format is set to Automatically Determine.

Set to False for all arrays except 30 microns single pack and multi pack, for which it is set to True.

50 Feature Extraction Reference Guide

1 Default Protocol Settings miRNA_1200_Jun14

Use Enhanced Gridding

An enhanced automatic gridding algorithm was released in Feature Extraction 12.1 for use in CGH protocols only. Agilent has not validated the new algorithm in miRNA protocols.

False

Optimize Grid Fit Grid Format The parameters and values for optimizing the grid differ depending on the format.

Automatically Determine

[Recognized formats: 65-micron feature size, 30-micron feature size, and Third Party]

Iteratively Adjust Corners? Hidden if Array Format is set to Automatically Determine.

True (All Formats, except Third Party)

False (Third Party)

Adjustment Threshold Hidden if Array Format is set to Automatically Determine.

0.300 (All Formats, except Third Party)

Maximum Number of Iterations Hidden if Array Format is set to Automatically Determine.

5 (All Formats, except Third Party)

Found Spot Threshold Hidden if Array Format is set to Automatically Determine.

0.200 (All Formats, except Third Party)

Number of Corner Feature Side Dimension?

Hidden if Array Format is set to Automatically Determine.

20 (All Formats, except Third Party)

Find Spots Spot Format Depending on the format selected by the software or by you, the default settings for this step change. See the following rows for the default values for finding spots.

Automatically Determine

[Recognized formats: same as those listed above except 244k 10uM replaces 65-micron feature size 10-micron scans]

Table 7 Default settings for miRNA_1200_Jun14 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

Default Protocol Settings 1 miRNA_1200_Jun14

Feature Extraction Reference Guide 51

Use the Nominal Diameter from the Grid Template

Hidden if Array Format is set to Automatically Determine.

True (All Formats)

Spot Deviation Limit Hidden if Array Format is set to Automatically Determine.

8.0 for all formats except for third party, for which it is set to 1.5

Calculation of Spot Statistics Method

Hidden if Array Format is set to Automatically Determine.

Use Cookie (All Formats)

Cookie Percentage Hidden if Array Format is set to Automatically Determine.

0.650 (Single Density, 25k)

0.561 (Double Density, 95k)

0.700 (185k, 185k 10 uM, 244k 10 uM, 65-micron feature size)

0.750 (30-micron feature size)

Exclusion Zone Percentage Hidden if Array Format is set to Automatically Determine.

1.200 (All Formats except 30-micron feature size)

1.300 (30-micron feature size)

Auto Estimate the Local Radius Hidden if Array Format is set to Automatically Determine.

True (Single Density, Double Density, 25k, 95k)

False (185k, 185k 10uM, 65-micron feature size, 30-micron feature size, 244k 10uM)

Table 7 Default settings for miRNA_1200_Jun14 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

52 Feature Extraction Reference Guide

1 Default Protocol Settings miRNA_1200_Jun14

LocalBGRadius Hidden if Array Format is set to Automatically Determine.

100 (when False for 185k, 185k 10uM, 65-micron feature size, 244k 10 uM)

150 (when False for 30-micron feature size)

Pixel Outlier Rejection Method Inter Quartile Region (Automatically Determine and All Formats)

RejectIQRFeat 1.42 (All Formats)

RejectIQRBG 1.42 (All Formats)

Statistical Method for Spot Values from Pixels Use Mean/Standard Deviation (Automatically Determine and All Formats)

Flag Outliers Compute Population Outliers True

Minimum Population 8

IQRatio 1.42

Background IQRatio 5.00

Use Qtest for Small Populations? True

Report Population Outliers as Failed in MAGEML file

False

Compute Non Uniform Outliers True

Scanner The values for the parameters change depending on the scanner used for the image. See the following for differences.

Automatically Determine

Agilent scanner

Automatically Compute OL Polynomial Terms Hidden if Array Format is set to Automatically Determine.

True

Table 7 Default settings for miRNA_1200_Jun14 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

Default Protocol Settings 1 miRNA_1200_Jun14

Feature Extraction Reference Guide 53

Feature (%CV)^2 0.04000

Red Poissonian Noise Term Multiplier

20

Red Signal Constant Term Multiplier

1

Green Poissonian Noise Term Multiplier

20

Green Signal Constant Term Multiplier

1

Background (%CV)^2 0.09000

Red Poissonian Noise Term Multiplier

3

Red Background Constant Term Multiplier

1

Green Poissonian Noise Term Multiplier

3

Green Background Constant Term Multiplier

1

Compute Bkgd, Bias and Error

Background Subtraction Method No Background Subtraction

Significance (for IsPosAndSignif and IsWellAboveBG) Use Error Model for Significance

2-sided t-test of feature vs. background max p-value

0.01

WellAboveMulti 13

Background Method by Format 244

Min Feature Threshold for Metrics 2000

Calculate Surface Fit (required for Spatial Detrend)

True

Feature Set for Surface Fit FeaturesInNegativeControlRange

Table 7 Default settings for miRNA_1200_Jun14 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

54 Feature Extraction Reference Guide

1 Default Protocol Settings miRNA_1200_Jun14

Perform Filtering for Surface Fit True

Perform Spatial Detrending True

Adjust Background Globally False

Perform Multiplicative Detrending False

Robust Neg Ctrl Stats? True

Choose universal error, or most conservative Use Universal Error Model

MultErrorGreen 0.1000

MultErrorRed 0.1000

Auto Estimate Add Error Red True

Auto Estimate Add Error Green True

Use Surrogates False

microRNA Analysis Output GeneView File True

Analyze By Effective Feat size True

Maximum Number of Features 10000

Minimum Number of Ratios 200

Low Signal Percentile 50.00

Is Gene Detected Multiplier 3.0

High Signal Percentile 90.00

Minimum Noise Multiplier 10.00

Throw away ratios greater than 1.50

Is Probe Detected Multiplier

3.0

Exclude non detected probes

True

Default Total Gene Signal if all probes are not detected

0.10

Table 7 Default settings for miRNA_1200_Jun14 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

Default Protocol Settings 1 miRNA_1200_Jun14

Feature Extraction Reference Guide 55

Set the Total Gene Signal to the Total Gene Error

False

Feature Size Fraction by Array Type Automatically Determine

Low Density 8-pack OR

High-Density 8-pack

Calculate Metrics Spikein Target Used True

Min Population for Replicate Stats? 5

Grid Test Format Automatically Determine

Recognized formats: 60 micron and 30 micron feature size, third party

Minimum percentage of features needed to be found

1.99 for 30 micron and 65 micron feature size

PValue for Differential Expression 0.010000

Percentile Value 75.00

Generate Results Type of QC Report miRNA

Generate Single Text File True

JPEG Down Sample Factor 4

Table 7 Default settings for miRNA_1200_Jun14 protocol (continued)

Protocol step Parameter Default Setting/Value (v12.2)

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1 Default Protocol Settings Differences in Protocol Settings Based on Each Step

Differences in Protocol Settings Based on Each Step

Some of the default settings are the same for all the protocols; yet, many are different, depending on the protocol step.

Table 8 shows each protocol step and where you can find information on the default settings for that step.

Table 8 Location of protocol template default settings for each step

Protocol step Location of default settings

Place Grid page 57

Optimize Grid Fit page 58

Find Spots page 59

Flag Outliers page 60

Compute Bkgd, Bias and Error

page 62

Correct Dye Biases page 65

Compute Ratios page 66

Calculate Metrics page 66

Generate Results page 66

Default Protocol Settings 1 Place Grid

Feature Extraction Reference Guide 57

Place Grid

The parameters and values differ depending on the selected microarray format.

Table 9 Place Grid Default values in common and differences for grid formats

Parameter Default values Formats using Default Value

Array Format Automatically Determine Single Density (11k, 22k), Double Density (44k), 95k, 185k, 65-micron feature size, 30-micron feature size single pack, 30-micron feature size multi pack, 185k, 10uM, 65-micron feature size 10-micron scans, 25k, Third Party

Placement Method Allow some distortion All

Enable background peak shifting?

False All except 30-micron feature size single pack and 30-micron feature size multi pack

Use central part of pack for slope and skew calculation?

False All except 30-micron feature size single pack and 30-micron feature size multi pack

Use the correlation method to obtain origin X of subgrids

False All except 30-micron feature size single pack and 30-micron feature size multi pack

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1 Default Protocol Settings Optimize Grid fit

Optimize Grid fit

The parameters and values differ depending on the microarray format.

Table 10 Optimize Grid fit Default values in common and differences for grid formats

Parameter Default values Formats using Default Value

Iteratively Adjust Corners? True

False

65-micron feature size 30-micron feature size

Third Party

Adjustment Threshold 0.300 (Not applicable for Third Party) 65-micron feature size 30-micron feature size

Maximum Number of Iterations 5 (Not applicable for Third Party) 65-micron feature size 30-micron feature size

Found Spots Threshold 0.200 (Not applicable for Third Party) 65-micron feature size 30-micron feature size

Number of Corner Features Side Dimension?

20 (Not applicable for Third Party) 65-micron feature size 30-micron feature size

Default Protocol Settings 1 Find spots

Feature Extraction Reference Guide 59

Find spots

The parameters and values differ depending on the microarray format.

Table 11 Find spots Default values in common and differences for spot formats

Parameter Default values Formats using Default Value

Use the Nominal Diameter from the Grid Template True All

Spot Deviation Limit 8.0 All except third party, where it is set to 1.5

Calculation of Spot Statistics Method Use Cookie All

Cookie Percentage 0.650 SD, 25k, TP

0.561 DD, 95k

0.700 185k, 185k 10uM, 65-micron feature size

0.750 30-micron feature size

Exclusion Zone Percentage 1.200 All

1.300 30-micron feature size

Auto Estimate the Local Radius True All

LocalBGRadius When False is the default, 100 185k, 185k 10uM, 65-micron feature size

When False is the default, 150 30-micron feature size

Pixel Outlier Rejection Method Inter Quartile Region All

RejectIQRFeat 1.42 All

RejectIQRBG 1.42 All

Statistical Method for Spot Values from Pixels Use Mean/Standard Deviation All

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1 Default Protocol Settings Flag outliers

Flag outliers

These parameters and values differ depending on the scanner used for the image, the microarray type, and the lab protocol.

Table 12 Flag Outliers Default values in common and differences for protocols

Parameter Default values Protocols using Default Value

Compute Population Outliers True All

Minimum Population 10 All except GE2-NonAT, ChIP, and miRNA

15 GE2-NonAT

8 ChIP and miRNA

IQRatio 1.42 All

Background IQRatio 1.42 All except miRNA

5.00 miRNA

Use Qtest for Small Populations? True All

Report Population Outliers as Failed in MAGEML file

False All

Compute Non Uniform Outliers True All

Agilent scanner

Automatically Compute OL Polynomial Terms True All except GE2-NonAT

Feature (%CV)^2 0.04000 All except GE2-NonAT

Red Poissonian Noise Term Multiplier

30 GE2

20 miRNA

5 CGH, ChIP

Red Signal Constant Term Multiplier

1 All except GE2-NonAT

Green Poissonian Noise Term Multiplier

20 GE1, GE2, miRNA

Default Protocol Settings 1 Flag outliers

Feature Extraction Reference Guide 61

5 CGH, ChIP

Green Signal Constant Term Multiplier

1 All except GE2-NonAT

Background (%CV)^2 0.09000 All except GE2-NonAT

Red Poissonian Noise Term Multiplier

3 All except GE1, GE2-NonAT

Red Signal Constant Term Multiplier

1 All except GE1, GE2-NonAT

Green Poissonian Noise Term Multiplier

3 All except GE2-NonAT

Green Background Constant Term Multiplier

1 All except GE2-NonAT

Automatically Compute OL Polynomial Terms False GE2-NonAT

Feature (%CV)^2 0.11000

Poissonian Noise Term 320 (R, G combined)

Background Term 600 (R, G combined)

Background (%CV)^2 0.09000

Poissonian Noise Term 320 (R, G combined)

Background Term 600 (R, G combined)

Table 12 Flag Outliers Default values in common and differences for protocols (continued)

Parameter Default values Protocols using Default Value

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1 Default Protocol Settings Compute Bkgd, Bias and Error

Compute Bkgd, Bias and Error

These parameters and values differ depending on the microarray type and the lab protocol.

Table 13 Compute Bkgd, Bias and Error Default values in common and differences for protocols

Parameter Default values Protocols using Default Value

Background Subtraction Method No Background Subtraction All except for GE2-NonAT

Local Background GE2-NonAT

Significance Use Error Model for Significance All except GE2-NonAT

Use Pixel Statistics for Significance GE2-NonAT

2-sided t-test of feature vs. background max p-value

0.01 All

WellAboveMulti 13 All except for GE2-NonAT

2.6 GE2-NonAT

Background Method by Format 244 miRNA only

Minimum Feature Threshold for Metrics

2000 miRNA only

Signal CorrectionCalculate Surface Fit (required for Spatial Detrend)

True All

Feature Set for Surface Fit FeaturesInNegativeControlRange GE1, GE2, miRNA

AllFeatureTypes GE2-NonAT

Only NegativeControl Features

CGH, ChIP

Perform Filtering for Surface Fit False CGH, ChIP

True GE1, GE2, GE2-NonAT, miRNA

Perform Spatial Detrending True All except GE2-NonAT

False GE2-NonAT

Default Protocol Settings 1 Compute Bkgd, Bias and Error

Feature Extraction Reference Guide 63

Signal CorrectionAdjust Background Globally False All except for GE2-NonAT which is set to True.

Signal CorrectionPerform Multiplicative Detrending

(not applicable for GE2-NonAT)

True GE1, GE2, CGH, ChIP

False miRNA

Detrend on Replicates Only False CGH, ChIP

True GE1, GE2

Filter Low signal probes from Fit? True GE1, GE2, CGH, ChIP

Neg. Ctrl. Threshold Mult. Detrend Factor

3 CGH, ChIP

5 GE1, GE2

Perform Filtering for Fit Use Window Average GE1, GE2, CGH, ChIP

Use polynomial data fit instead of LOESS?

True GE1, CGH, ChIP

Polynomial Multiplicative DetrendDegree

4 GE1, CGH, ChIP

Robust Neg Ctrl Stats? False GE1, GE2, GE2-NonAT

True CGH, ChIP, miRNA

Choose universal error, or most conservative Most Conservative All except for miRNA

Use Universal Error Model miRNA

MultErrorGreen 0.1000 All except for GE2-NonAT

.0900 GE2-NonAT

MultErrorRed 0.1000 All except GE1 protocol and GE2-NonAT

.0900 GE2-NonAT

Auto Estimate Add Error Red True All except GE1 protocol and GE2-NonAT

Table 13 Compute Bkgd, Bias and Error Default values in common and differences for protocols (continued)

Parameter Default values Protocols using Default Value

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1 Default Protocol Settings Compute Bkgd, Bias and Error

False (Additive Error Value Red-30) GE2-NonAT

Auto Estimate Add Error Green True All except for GE2-NonAT

False (Additive Error Value Green-30)

GE2-NonAT

Use Surrogates True All except for miRNA

False miRNA

Table 13 Compute Bkgd, Bias and Error Default values in common and differences for protocols (continued)

Parameter Default values Protocols using Default Value

Default Protocol Settings 1 Correct Dye Biases

Feature Extraction Reference Guide 65

Correct Dye Biases

These parameters and values differ depending on the microarray type. The GE1 protocol and the miRNA protocol do not correct for dye biases.

Table 14 Correct Dye Biases Default values in common and differences for protocols

Parameter Default values Protocols using default values (NA for GE1 and miRNA protocols)

Use Dye Norm List Automatically Determine All

Dye Normalization Probe Selection Method Use Rank Consistent Probes All

Rank Tolerance 0.050 All

Variable Rank Tolerance False All

Omit Background Population Outliers False All

Allow Positive and Negative Controls False All

Signal Characteristics OnlyPositiveAndSignificantSignals All

Normalization Correction Method Linear and Lowess GE2

Linear CGH, ChIP

Lowess Only GE2-NonAT

Max Number Ranked Probes -1 All except for GE2

8000 GE2

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1 Default Protocol Settings Compute ratios, calculate metrics, and generate results

Compute ratios, calculate metrics, and generate results

Some of these parameters and values are the same for all the protocols, others vary, and still others do not even use a protocol step.

Table 15 Values in common and differences in protocols

Protocol step Parameter Default Value (v12.2)

Compute Ratios Peg Log Ratio Value 4.00 (Not applicable for GE1 and miRNA)

Calculate Metrics Spikein Target Used? True (GE1, GE2, miRNA)

False (CGH, ChIP, GE2-NonAT)

Min Population for Replicate Statistics 5 (3 for CGH and ChIP)

Grid Test Format Automatically Determine (Not applicable for GE2-NonAT)

PValue for Differential Expression 0.010000 (All)

Percentile Value 75.00 (All)

Generate Results Type of QC Report Gene Expression for GE1 or GE2, Streamlined CGH for CGH, CGH_ChIP for ChIP, miRNA for miRNA

Generate Results Generate Single Text File True (All)

JPEG Down Sample Factor 4 (All)

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2 QC Report Results

QC Reports 68

QC Report Headers 87

Feature Statistics 90

Histogram of LogRatio plot 103

QC Report Results in the FEPARAMS and Stats Tables 121

QC Metric Set Results 122

QC reports include statistical results to help you evaluate the reproducibility and reliability of your single microarray data. This chapter describes each of five types of QC report 2- color Gene Expression, 1- color Gene Expression, Streamlined CGH, CGH_ChIP, and microRNA (miRNA) and how each can help you interpret the performance of your microarray system. Use plots and statistics from the report to:

Set up your own run charts of statistical values versus time or experiment number to track performance of one microarray compared to other microarrays

Monitor upstream lab protocols, such as performance of your hybridization/washing steps

Monitor the effect of changing Feature Extraction protocol parameters on the performance of your data analysis

If you incorporate a set of QC metrics in your extraction, those results appear on the final page of the QC report as an Evaluation Table.

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QC Reports

This section contains example QC Reports, and points out the different sections that appear on the reports.

NOTE The reports in this section are examples. The actual contents of the reports vary, depending on the protocol settings and QC metric set used.

QC Report Results 2 2-color Gene Expression QC Report

Feature Extraction Reference Guide 69

2-color Gene Expression QC Report

This module shows you the organization of the 2- color gene expression QC report. See the following figure and the figures on the next pages for links to information on the QC Report regions.

Figure 1 2-color Gene Expression QC Report with Spike-ins (p1)

1QC Report Headers on page 87

2 Spot finding of Four Corners on page 90

3 Outlier Stats on page 91

6 Plot of Background-Corrected Signals on page 95

4 Spatial Distribution of All Outliers on page 91

5 Net Signal Statistics on page 93

1

2

3

4

5

6

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2 QC Report Results 2-color Gene Expression QC Report

Figure 2 2-color Gene Expression QC Report with Spike-ins (p2)

10 Foreground Surface Fit on page 97

12 Reproducibility Statistics (%CV Replicated Probes) on page 104

13 Microarray Uniformity (2-color only) on page 106

14 Sensitivity on page 107

8 Spatial Distribution of Significantly Up-Regulated and Down-Regulated Features (Positive and Negative Log Ratios) on page 100

11 Plot of LogRatio vs. Log ProcessedSignal on page 101

7 Negative Control Stats on page 94

15 Reproducibility plot for 2-color gene expression (spike-in probes) on

9 Local Background Inliers on page 97

7

10

9

11

8

13

14

12

15

QC Report Results 2 2-color Gene Expression QC Report

Feature Extraction Reference Guide 71

Figure 3 2-color Gene Expression QC Report with Spike-ins (p3)

17

16

18

16 2-color gene expression spike-in signal statistics on page 111

17 Spike-in Linearity Check for 2-color Gene Expression on page 113

18 QC Metric Set Results on page 122

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1-color Gene Expression QC Report

This module shows you the organization of the 1- color gene expression QC report. See the following figure and the figures on the next pages for links to information on each of the QC Report regions.

Figure 4 1-color Gene Expression QC Report with Spike-ins (p1)

1QC Report Headers on page 87

2 Spot finding of Four Corners on page 90

3 Outlier Stats on page 91

1

2

4

34 Spatial Distribution of All Outliers on page 91

5 Net Signal Statistics on page 93

5

6 Histogram of Signals Plot (1-color GE or CGH) on page 96

6

QC Report Results 2 1-color Gene Expression QC Report

Feature Extraction Reference Guide 73

Figure 5 1-color Gene Expression QC Report with Spike-ins (p2)

8 Local Background Inliers on page 97

11 Reproducibility Statistics (%CV Replicated Probes) on page 104

10Multiplicative Surface Fit on page 99

12 1-color gene expression spike-in signal statistics on page 112

9 Foreground Surface Fit on page 97

13 Spatial Distribution of Median Signals for each Row and Column on page 102

7 Negative Control Stats on page 94

7

8

9

10

11

12

13

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2 QC Report Results 1-color Gene Expression QC Report

Figure 6 1-color Gene Expression QC Report with Spike-ins (p3)

14 Reproducibility plot for 1-color gene expression (spike-in probes) on page 109

15 Spike-in Linearity Check for 1-color Gene Expression on page 114

1514

16 QC Metric Set Results on page 122

17 Table of Values for Concentration-Response Plot (1-color only) on page 115

16

17

QC Report Results 2 Streamlined CGH QC Report

Feature Extraction Reference Guide 75

Streamlined CGH QC Report

The streamlined CGH QC report provides QC metrics that are relevant to CGH application. All log plots use log base 2 (not 10).

Figure 7 Streamlined CGH QC Report (p1)

1 QC Report Headers on page 87

2 Spot finding of Four Corners on page 90

3 Spatial Distribution of All Outliers on page 91

4QC reports with metric sets added on page 83

5 Histogram of Signals Plot (1-color GE or CGH) on page 96

1

2

3

4

5

6 6 Outlier Stats on page 91

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2 QC Report Results Streamlined CGH QC Report

Figure 8 Streamlined CGH QC Report (p2)

8 Plot of Background-Corrected Signals on page 95

8

7Spatial Distribution of Significantly Up-Regulated and Down-Regulated Features (Positive and Negative Log Ratios) on page 100

7

QC Report Results 2 CGH_ChIP QC Report

Feature Extraction Reference Guide 77

CGH_ChIP QC Report

This report lists all of the same information as the 2- color Gene Expression report but removes the Array Uniformity table and spike- ins and has a Histogram of LogRatio plot. All log plots use log base 2 (not 10).

Figure 9 CGH_ChIP QC Report (p1)

1QC Report Headers on page 87

2 Spot finding of Four Corners on page 90

3 Outlier Stats on page 91

4 Spatial Distribution of All Outliers on page 91

7 Plot of Background-Corrected Signals on page 95

5 Net Signal Statistics on page 93

6 Negative Control Stats on page 94

1

2

3

5

6

4 7

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2 QC Report Results CGH_ChIP QC Report

Figure 10 CGH_ChIP QC Report (p2)

11 Spatial Distribution of Significantly Up-Regulated and Down-Regulated Features (Positive and Negative Log Ratios) on page 100

12 QC reports with metric sets added on page 83

9 Foreground Surface Fit on page 97

8 Local Background Inliers on page 97

10 Reproducibility Statistics (%CV Replicated Probes) on page 104

13 Plot of LogRatio vs. Log ProcessedSignal on page 101

14 Histogram of LogRatio plot on page 103

9

10

12

13

11 8

14

QC Report Results 2 MicroRNA (miRNA) QC Report

Feature Extraction Reference Guide 79

MicroRNA (miRNA) QC Report

Agilent miRNA microarrays are currently in development. Check the Agilent website for the latest information.

This module shows you the organization of the 1- color miRNA QC report. See the following figure and the figures on the next pages for links to information on each of the QC Report regions.

Figure 11 MicroRNA (miRNA) QC Report (p1)

1 QC Report Headers on page 87

2 Spot finding of Four Corners on page 90

3 Outlier Stats on page 91

4 Spatial Distribution of All Outliers on page 91

5 Net Signal Statistics on page 93

7 Histogram of Signals Plot (1-color GE or CGH) on page 96

6 Negative Control Stats on page 94

5 2

3

4 7

1

6

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2 QC Report Results MicroRNA (miRNA) QC Report

Figure 12 MicroRNA (miRNA) QC Report (p2)

9 Reproducibility Statistics (%CV Replicated Probes) on page 104

8

10

12

8 Foreground Surface Fit on page 97

11 QC reports with metric sets added on page 83

10 Reproducibility plot for miRNA (non-control probes) on page 110

12 Spatial Distribution of Median Signals for each Row and Column on page 102

9

11

QC Report Results 2 Non-Agilent GE2 QC Report

Feature Extraction Reference Guide 81

Non-Agilent GE2 QC Report

This report lists all of the same information as the 2- color gene expression QC report but with no spike- ins.

Figure 13 Non-Agilent GE2 QC Report (p1)

1 QC Report Headers on page 87

2 Spot finding of Four Corners on page 90

3 Outlier Stats on page 91

4 Spatial Distribution of All Outliers on page 91

7 Plot of Background-Corrected Signals on page 95

5 Net Signal Statistics on page 93

6 Negative Control Stats on page 94

2

3 6

4

5

7

1

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2 QC Report Results Non-Agilent GE2 QC Report

Figure 14 Non-Agilent GE2 QC Report (p2)

12 Spatial Distribution of Significantly Up-Regulated and Down-Regulated Features (Positive and Negative Log Ratios) on page 100

13 Plot of LogRatio vs. Log ProcessedSignal on page 101

9 Foreground Surface Fit on page 97

8 Local Background Inliers on page 97

10 Reproducibility Statistics (%CV Replicated Probes) on page 104

11 Microarray Uniformity (2-color only) on page 106

8 12

13

9

10

11

QC Report Results 2 QC reports with metric sets added

Feature Extraction Reference Guide 83

QC reports with metric sets added

When metric sets are associated to the protocols, QC reports are generated with an additional set of evaluation metrics. Depending on the microarray types, some QC metric sets come with thresholds (denoted by QCMT) and some without thresholds (denoted by QCM).

If thresholds are included in the metric set, the evaluation tables in the QC report show metrics that are within threshold ranges or that have exceeded those ranges.

Agilent has determined which of the FE Stats are good metrics to follow the processing of Agilent arrays. Most of the metrics chosen are useful to determine if there are problems in the various laboratory steps (label, hybridization, wash, scan steps). The new IsGoodGrid metric tracks the automatic grid- finding of Feature Extraction. By looking at numerous data run on our arrays, using our wet- lab protocols, Agilent has found thresholds that indicate if the data is in the expected range (Good) or out of the expected range (Evaluate).

For some applications (CGH, miRNA), an extra threshold level, Excellent is provided. More data has been screened to allow setting the metric thresholds to tighter limits that indicate excellent processing. For those applications that do not have a full set of thresholds (for example, ChIP), or no Excellent thresholds (for example, GE1 and GE2), the user is assured that the data coming from the Good grade is good to use. Excellent thresholds for those applications may be provided in the future.

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2 QC Report Results QC reports with metric sets added

QC metric set results--default protocol settings

Figure 15 is an example of part of a QC report the header and the Evaluation Metrics table generated from a 2- color gene expression extraction whose GE2 metric set with thresholds had been added. In this extraction, the default protocol settings were used. Note that all values for the metrics are within the default threshold ranges.

Figure 15 Partial QC ReportHeader and Evaluation Metrics with GE2 metric set with thresholds addedDefault protocol settings

QC Report Results 2 QC reports with metric sets added

Feature Extraction Reference Guide 85

QC metric set resultsSpatial and Multiplicative Detrending Off

Figure 16 is an example of a QC report header and Evaluation Metrics table generated from a 2- color gene expression extraction whose GE2 metric set with thresholds were added. In this extraction spatial and multiplicative detrending were turned off. Note that not all values of the metrics are within the default thresholds.

Figure 16 QC Report Header and Evaluation Metrics with GE2 metric set with thresholds addedDetrending turned off

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2 QC Report Results QC reports with metric sets added

QC metric set resultsmiRNA spike-in analysis

Figure 17 is an example of a QC report header and Evaluation Metrics table generated from a 1- color extraction whose miRNA metric set with thresholds had been added. In this extraction, the default protocol settings were used. Note that not all values of the metrics are within the default thresholds. For details on how the miRNA spike- in statistics and metrics are calculated, see MicroRNA Analysis on page 285.

Figure 17 QC Report Header and Evaluation Metrics with miRNA metric set with thresholds added - Default protocol settings

QC Report Results 2 QC Report Headers

Feature Extraction Reference Guide 87

QC Report Headers

2-color Gene Expression QC Report

The following Feature Extraction information is found in the 2- color gene expression QC Report header:

Date Date and time that the QC Report was generated

Image Name of the TIFF file that was extracted

Protocol Name of the protocol used for the extraction

User Name Name of the user who set up the extraction

Grid Name of the grid template or grid file used

FE Version Version of the Feature Extraction software used

Sample (red/green) Names of Cy5- and Cy3- labeled samples

DyeNorm List Name of the dye normalization list

No of Probes in DyeNorm List

Number of probes in the designated dye normalization probe list

BG Method Type of background subtraction method used

Background Detrend

If Spatial Detrend was turned on or off during the extraction

Multiplicative Detrend

If Multiplicative Detrend was turned on or off during the extraction

Dye Norm Type of dye normalization method used

Linear DyeNorm Factor Global dye normalization factor determined for the linear portion of the correction method.

Additive Error Additive portion of the error estimated in the Universal or Most Conservative error model (if AutoEstimateAddError was selected). Or, the values entered into the protocol, (if AutoestimateAddError was not selected). Note that the

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2 QC Report Results 1-color Gene Expression QC Report

additive error that appears in the QC report header is the Additive Error value selected in the protocol multiplied by the linear dye norm factor.

Saturation Value

The signal intensity value above which the signal is considered saturated. This value only appears if it exceeds about 65,500. If it appears, this means that this QC report is from an XDR image file.

1-color Gene Expression QC Report

This report lists all of the same header information as the 2- color gene expression report, except for Dye Norm and Linear DyeNorm Factor which are removed.

Streamlined CGH QC Report

The streamlined CGH QC report contains the same header information as the 2- color gene expression QC report, except for Linear DyeNorm Factor and Additive Error which are removed. Also, the information from the two fields, BG Method and Background Detrend, have been collapsed into the one field, BG Method.

CGH_ChIP QC Report

All header information that appears in the 2- color gene expression QC report are included in the CGH_ChIP report. This report lists one additional metric, Derivative of Log Ratio Spread in the header information.

Derivative of Log Ratio Spread

Measures the standard deviation of the probe- to- probe difference of the log ratios. This metric is used in CGH experiments where differences in the log ratios are small on average. A smaller standard deviation here indicates less noise in the biological signals.

QC Report Results 2 MicroRNA (miRNA) QC Report

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MicroRNA (miRNA) QC Report

This header lists the same information as the 1- color gene expression QC Report header. If the XDR function is turned on, it also lists Saturation Values exceeding 65,500. Because the dynamic range of the intensity for all miRNA microarray spots on a microarray may exceed that of a normal scan range, the miRNA analysis on some microarrays can benefit with the XDR function turned on.

Non-Agilent 2-color gene expression QC Report

This header lists the same information as the 2- color gene expression QC report header.

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Feature Statistics

This section provides an explanation for each of the feature statistics segments of the QC report and how these feature statistics can help you assess the performance of your microarray system.

Spot finding of Four Corners

By looking at the features in the four corners of the microarray, you can decide if the spot centroids have been located properly. If their locations are off- center in one or more corners, you may have to run the extraction again with a new grid.

Figure 18 QC ReportSpot Finding for Four Corners

QC Report Results 2 Outlier Stats

Feature Extraction Reference Guide 91

Outlier Stats

If the QC Report shows a greater than expected number of nonuniform or population outliers, check your hybridization/wash step. Also, check the visual results (.shp file) to see if the spot centroids are off- center. If the grid was not placed correctly, a new grid is required.

Figure 19 QC ReportOutlier Stats

For 1- color reports, the number of outliers is reported for the green channel only.

Spatial Distribution of All Outliers

The QC report shows two plots of all the outliers, both population and nonuniformity outliers, whose positions are distributed across the microarray. One plot is for the green channel, and the other, for the red channel. SNP probes are included.

To distinguish the background population and nonuniform outliers from one another, look at the color coding at the bottom of the two plots.

For the 1- color report, only the green plot is shown.

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2 QC Report Results Spatial Distribution of All Outliers

Figure 20 QC ReportNumber and Spatial Distribution of Outliers

The number (and percentage) of features that are feature nonuniformity outliers in either the green or red channel is shown under the plot. The 1- color report shows only the percentage of green feature non- uniformity outliers.

Also, the number (and percentage) of genes that are nonuniformity outliers in either channel is shown under the plot. If there were replicate features representing one gene and at least one feature was not an outlier, no gene outliers would appear.

QC Report Results 2 Net Signal Statistics

Feature Extraction Reference Guide 93

Net Signal Statistics

Net signal is the mean signal minus the scanner offset. Net

signal is used so that these statistics are independent of the

scanner version.

Net signal statistics are an indication of the dynamic range of the signal on a microarray for both non- control probes and spike- in probes (not applicable for CGH QC report). The QC Report uses the range from the first percentile to the 99th percentile as an indicator of dynamic range for that microarray. NetSignal is also a column in the FeatureData output.

For example, in Figure 21 for non- control probes, the dynamic range of the net signal intensity for the red channel is from 42 to 6803. Half the probes have a net signal intensity of greater than the median of 97 and half below the median of 97. The median (or 50th percentile) represents the middle of the ranked- values of the distribution of signals.

Another indicator of signal range for the microarray is the number of features that are saturated in the scanned image (for example, NumSat).

Figure 21 QC ReportNet Signal Statistics

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2 QC Report Results Negative Control Stats

Negative Control Stats

The Negative Control Stats table includes the average and standard deviation of the net signals (mean signal minus scanner offset) and the background- subtracted signals for both the red and green channels in the negative controls. These statistics filter out saturated and feature nonuniform and population outliers and give a rough estimate of the background noise on the microarray. SNP probes are not included in these statistics.

Figure 22 QC ReportNegative Control Stats

QC Report Results 2 Plot of Background-Corrected Signals

Feature Extraction Reference Guide 95

Plot of Background-Corrected Signals

Figure 23 is a plot of the log of the red background- corrected signal versus the log of the green background- corrected signal for non- control inlier features. The linearity or curvature of this plot can indicate the appropriateness of background method choices. The plot should be linear.

The intersection of the red vertical and horizontal lines shows the location of the median signal. The numbers along the edge of the lines represent the location of the median signal on the plot.

The values under the plot indicate the number of non- control features that have a background- corrected signal less than zero. SNP probes are not included.

Figure 23 QC ReportPlot of Background-Corrected Signals

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2 QC Report Results Histogram of Signals Plot (1-color GE or CGH)

Histogram of Signals Plot (1-color GE or CGH)

The purpose of this histogram is to show the level of signal and the shape of the signal distribution. The histogram is a line plot of the number of points in the intensity bins vs. the log of the processed signal. SNP probes are not included.

Figure 24 1-color QC ReportHistogram of Signals Plot

QC Report Results 2 Local Background Inliers

Feature Extraction Reference Guide 97

Local Background Inliers

With these numbers, you can see the mean signal distribution for the local background regions (BGMeanSignal) after outliers have been removed. This information can help you detect hybridization/wash artifacts and can be a component of noise in the low signal range. SNP probes are included.

Figure 25 QC ReportLocal Background Inliers

Foreground Surface Fit

See Step 13. Perform background spatial detrending to fit a surface on page 258 of this guide for more information about these calculations.

Spatial Detrend attempts to account for low signal background that is present on the feature foreground and varies across the microarray. SNP probes are not included.

A high RMS_Fit number can indicate gradients in the low signal range before detrending.

RMS_Resid indicates residual noise after detrending.

AvgFit indicates how much signal is in the foreground.

A higher AvgFit number indicates that a larger amount of signal was detected by the detrend algorithm and removed.

This value may include the scanner offset, unless a background method has been used before detrending. The value may not include higher frequency background signals. These higher frequency background signals are best removed by using the Local Background Method before the detrending algorithm.

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Figure 26 QC ReportForeground Surface Fit

QC Report Results 2 Multiplicative Surface Fit

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Multiplicative Surface Fit

See Step 16. Determine the error in the signal calculation on page 268 of this guide for more information about these calculations.

This value is the root mean square (RMS) of the surface fit for the data. The RMS X 100 is roughly the average % deviation from flat on the microarray. A multiplicative trend means that there are regions of the microarray that are brighter or dimmer than other regions. This trend is an effect that multiplies signals; that is, a brighter signal is more affected in absolute signal counts than a dimmer signal. SNP probes are not included in calculation of multiplicative detrending.

This option is turned on in GE1, GE2, and CGH protocols, turned off in the miRNA protocol and is not available for non- Agilent protocols.

If the signal is improved through a multiplicative surface fit, the RMS_Fit value appears as a fraction, as in the figure shown.

Figure 27 QC ReportMultiplicative Surface Fit

What if multiplicative detrending does not work?

If the median %CV for the Processed Signal of the non- control probes is greater than the BGSub Signal median %CV after multiplicative detrending, Feature Extraction turns off multiplicative detrending.

If multiplicative detrending did not result in better data, the QC report shows an RMS_Fit = 0.0.

If there are no stats for non- control probes, Feature Extraction looks at the spike- in control probes. If the %CVs for these become worse, Feature Extraction removes detrending.

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2 QC Report Results Spatial Distribution of Significantly Up-Regulated and Down-Regulated Features (Positive and Negative

Log Ratios)

If the option Detrend on Replicates only is chosen and if there are not enough replicates for non- control or spike- in control probes, Feature Extraction turns off multiplicative detrending.

Spatial Distribution of Significantly Up-Regulated and Down-Regulated Features (Positive and Negative Log Ratios)

You can display the distribution of the significantly up- and down- regulated features on this plot (upred; downgreen).

Figure 28 QC ReportSpatial Distribution of Up- and Down-Regulated Features

For the CGH QC Report, this plot is referred to as Spatial Distribution of the Positive and Negative Log Ratios.

If the microarray contains greater than 5000 features, the software randomly selects 5000 data points. These points include the number of up- regulated features in the same proportion to the number of down- regulated features as they are found on the actual microarray.

The threshold that is used to determine significance is set in the protocolQCMetrics_differentialExpressionPValue.

These are the same features shown as up- or down- regulated in Figure 29.

QC Report Results 2 Plot of LogRatio vs. Log ProcessedSignal

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Plot of LogRatio vs. Log ProcessedSignal

This plot shows the log ratios of non- control inliers vs. the log of their red and green processed signals. The color coding signifies the degree to which features are significantly differentially expressed: those that are up- regulated (red), those that are down- regulated (green) and those that cannot confidently be said to show gene expression (light yellow).

For the CGH QC Report, these are referred to as Positive, Negative log ratios (base 2). The threshold that is used to determine significance is set in the protocol (QCMetrics_differentialExpressionPValue).

Features that were used for normalization are indicated in blue. Significance takes precedence over normalization for the color coding; that is, features that are both significantly differentially expressed and used for normalization are color- coded either red or green. SNP probes are not included.

LogProcessedSignal in the plot is [Log(rProcessedSignal x gProcessedSignal)]/2.

Figure 29 QC ReportPlot of Up- and Down-Regulated Features

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2 QC Report Results Spatial Distribution of Median Signals for each Row and Column

Spatial Distribution of Median Signals for each Row and Column

The first of these graphs plots the median Processed Signal and median BGSub Signal for each row over all columns of a 1- color GE microarray. The second plots the same signals for each column over all rows of the 1- color GE microarray. The difference between the Processed Signal and the BGSubSignal represents the effect of the multiplicative detrending. The Processed Signal should look flatter.

Higher frequency noise is shown in these plots so you can distinguish a low frequency trend outside of the high frequency noise.

Figure 30 1-color QC ReportMedian Signal Spatial Distribution

QC Report Results 2 Histogram of LogRatio plot

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Histogram of LogRatio plot

This is a plot of the log ratio distributions, and displays the log ratios vs. the number of probes. This plot is included only in the CGH_ChIP report, which is the default report for the ChIP_ _ protocol.

Figure 31 Histogram of LogRatio plot

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Inter-Feature Statistics

Spike-in probes are known probes that are hybridized with

known quantities of a target spike-in cocktail. They are

used to perform a quality check of the microarray/experiment.

Some microarray designs have replicated non- control probes; that is, multiple features on the microarray contain the same probe sequence. Many of the Agilent microarray designs also have spike- in probes, which are replicated across the microarray (for example, some microarrays have 10 sequences with 30 replicates each). The QC Report uses these replicated probes to evaluate reproducibility of both the signals and the log ratios. Metrics such as signal %CV and log ratio statistics are calculated if probes are present with a minimum number of replicates.

The protocol indicates if labeled target to these spike- in probes has been added in the hybridization (QCMetrics_UseSpikeIns). The minimum number of replicates (inliers to Sat & NonUnif flagging) is also set in the protocol (QCMetrics_minReplicate Population).

This section provides an explanation for each of the segments of the QC report that cover interfeature statistics and how these replicate statistics can help you assess performance.

Reproducibility Statistics (%CV Replicated Probes)

Non-control probes

If a non- control probe has a minimum number of inliers, a %CV (percent coefficient of variation) of the background- corrected signal is calculated for each channel (SD of signals/average of signals). This calculation is done for each replicated probe, and the median of those %CVs is reported in the table for each channel. SNP probes are not included.

QC Report Results 2 Reproducibility Statistics (%CV Replicated Probes)

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Figure 32 QC ReportReproducibility

A lower median %CV value indicates better reproducibility of signal across the microarray than a higher value.

Exclusion of dim probes

Feature Extraction calculates the Median %CV using those probes bright enough to be in the range where the noise is more proportional to signal. Feature Extraction excludes from the calculation any sequences for which the Average (BGSubSignal) x Multiplicative error < Additive error/Dye Norm Factor. For 1- color data the Dye Norm Factor is 1.

A probe sequence has a %CV calculated if the number of features that pass the filters (NonUniform and signal filter, described above) is greater than the minimum replicate number indicated in the protocol: QCMetrics_minReplicatePopulation.

If the number of replicated sequences with enough inlier features is less than 10 or less than 10% of the replicated sequence, that is, if there are not enough bright replicated probes, the Median %CV field shows up as - 1.

Spike-in probes

The same algorithm is used to calculate the Median %CV for the spike- in probes as well. Because there are only ten sequences in total and some are expected to fail the Additive error test described above, the minimum number of bright enough sequences required to calculate the Median %CV is 3.

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Microarray Uniformity (2-color only)

The QC Report has two metrics that measure the uniformity of replicated log ratios and that indicate the span of log ratios: average S/N and AbsAvgLogRatio. These are calculated from inlier features of replicated non- control and spike- in probes.

For example, some microarrays have 100 different non- control probe sequences with 10 replicate features each. For each replicate probe, the average and SD of the log ratios are calculated. The signal to noise (S/N) of the log ratio for each probe is calculated as the absolute of the average of the log ratios divided by the SD of the log ratios. From the population of 100 S/Ns, for example, the average S/N is determined and shown in Figure 33.

The second metric, AbsAvgLogRatio, indicates the amount of differential expression (up- regulated or down- regulated). As described above, averages of log ratios are calculated for each replicated probe. The absolute of these averages is determined next. Then, the average of these absolute of averages is calculated to get a single value for the QC Report. The larger this value, the more differential expression is present.

Figure 33 QC ReportArray Uniformity: LogRatios

QC Report Results 2 Sensitivity

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Sensitivity

These values represent the NetSignal to background (BGUsed - ScannerOffset) ratio of the two spike- in probes with the lowest background- subtracted signal. Their purpose is to characterize the sensitivity of detecting a low signal relative to the background.

Figure 34 QC ReportSensitivity: Agilent SpikeIns Ratio of Signal to Background for 2 dimmest probes

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Reproducibility Plots

Reproducibility plot for 2-color gene expression (spike-in probes)

Signal replicate statistics are calculated for spike- in probes if three criteria are met:

They are present on the microarray.

The protocol indicates that labeled target to these spike- in probes has been added in the hybridization (QCMetrics_UseSpikeIns is True).

There are a minimum number of inlier features for calculations (QCMetrics_minReplicatePopulation).

As described above for non- control probes, %CVs are calculated for inliers for both red and green background- corrected signals. The %CV for each probe is plotted on the next page vs. the average of its background- corrected signal. The median of these %CVs is shown directly beneath the plot.

Figure 35 QC ReportAgilent SpikeIns: %CV of Average BGSub Signal

QC Report Results 2 Reproducibility Plots

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Reproducibility plot for 1-color gene expression (spike-in probes)

This graph plots %CV vs. the log_gMedianProcessedSignal for the 1- color gene expression microarray experiment. The region where the %CV flattens out and is not tightly correlated with signal is the range where noise is proportional to signal. This is generally the range used to calculate the median %CV.

Figure 36 1-color QC ReportAgilent SpikeIns: %CV of Avg. Processed Signal Plot

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Reproducibility plot for miRNA (non-control probes)

This graph plots %CV vs. the log_gMedianProcessedSignal for the 1- color miRNA microarray experiment. The region where the %CV flattens out and is not tightly correlated with signal is the range where noise is proportional to signal. This is generally the range used to calculate the median %CV.

Figure 37 miRNA QC Report Reproducibility: % CV for Replicated Probes

QC Report Results 2 Spike-in Signal Statistics

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Spike-in Signal Statistics

2-color gene expression spike-in signal statistics

These signal statistics and S/N values for spike- ins indicate accuracy and reproducibility of the signals of the microarray probes. The table shows the expected signal of the spike- in probe, the observed average signal, the SD of the observed signal and the S/N of the observed signal.

Figure 38 2-color QC ReportAgilent SpikeIns Signal Statistics

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1-color gene expression spike-in signal statistics

For each sequence of spike- ins this table shows the Probe Name, the median Processed Signal (median of LogProcessedSignal), %CV (SD_ProcessedSignals/Avg_ProcessedSignals) and StdDev (of LogProcessedSignals).

Figure 39 1-color QC ReportAgilent SpikeIns Signal Statistics

QC Report Results 2 Spike-in Linearity Check for 2-color Gene Expression

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Spike-in Linearity Check for 2-color Gene Expression

Using the data calculated for the above table, the observed average log ratio is plotted vs. the expected log ratio for each of the spike- in probes. A linear regression analysis is done using these values and the metrics are shown beneath the plot. A slope of 1, y- intercept of 0 and R2 of 1 is the ideal of such a linear regression. A slope < 1 may indicate compression, such as having under- corrected for background. The regression coefficient (R2) reflects reproducibility.

The standard deviation for each data point is shown on the plot by an error bar extending above and below the point.

Figure 40 QC ReportAgilent SpikeIns: Expected Log Ratio Vs. Observed LogRatio

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Spike-in Linearity Check for 1-color Gene Expression

This plot shows the dose/response curve of the spike- ins from the detection limit to the saturation point.

This plot is usually sigmoidal with two asymptotes, one at the scanner saturation point and one at the level of signal for sequences with no specifically bound target. Some microarrays produce plots missing the top asymptote, especially if extended dynamic range is used. (See Figure 41.)

At high signal levels the error bars are small since the scanner reaches saturation at this point. Both the signals and standard deviations are underestimated because the saturated data is not excluded from the calculation.

At low signal levels the error bars are visible because the signal is dropping into the background noise. The signal level at the top of the error bars of the features with lowest signal provides a rough estimate of the lower limit of detection. Signals at this level can be slightly overestimated and the error slightly underestimated because the signals below zero are excluded from the calculation.

The most reliable Feature Extraction data is found in the signal range where the signal increases linearly with the concentration of the target.

Figure 41 1-color QC ReportAgilent SpikeIns: Log (Signal) vs. Log (Relative concentration) Plot

QC Report Results 2 Spike-in Linearity Check for 1-color Gene Expression

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Table of Values for Concentration-Response Plot (1-color only)

This table presents the values for the log signal vs. log concentration plot shown in Figure 41.

Figure 42 1-color QC ReportAgilent Spike-In Concentration- Response Statistics

Detection of missing spike-ins

This section describes how Feature Extraction deals with missing spike- ins.

Case 1. If the array has a Grid Template with NO SpikeIns in the design,

If standard protocol is run, then Feature Extraction will give a Warning in the Summary Report that there are no SpikeIn probes.

If protocol has SpikeIn Used set to False, then the QC metric table in the QC Report will show - for values, and black font (instead of red, green, or blue fonts) indicating no evaluation has been done by Feature Extraction. Specialized SpikeIn plots & tables will be omitted from the report.

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Case 2. If the array has a Grid Template WITH SpikeIns in the design, but the user adds no SpikeIns to hyb,

If standard protocol is run, the results will either be wrong values or listed as NA.

If the protocol has SpikeIn Used set to False then the QC metric table in the QC Report will show - for values, and black font (instead of red, green, or blue fonts) indicating no evaluation has been done by Feature Extraction. Specialized SpikeIn plots & tables will be omitted from the report.

How the curve and statistics are calculated

Curve fit equation All of the statistics in the table above are calculated using a parameterized sigmoidal curve fit to the data.

where min is the level of signal for sequences with no specifically bound target and max is the upper limit of detection

where x0 is the center of the data and close to the center of the linear range

where w is the width of the curve on either side of x0.

Curve fit calculations Before the calculations the following assumptions are made:

Saturation Point is fixed or close to scanner detection limit. This value is Log(Scanner Saturation Value) = 4.82.

The linear range of the curve, (x0- w) (x0+w), does not define the dynamic range of the data as the data is close to linear for higher multiples of w away from x0.

F x min max min

1 e x x0 w

+ ----------------------------------------+=

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The asymptotes for the max and the min are not necessarily symmetric. The upper asymptote is a function of scanner offset, and the lower asymptote is a function of chemistry/scanner noise.

The calculations then follow this order:

a The Min is estimated by taking all the SpikeIn data and for each sequence calculating the BackgroundSubtracted- SignalAverage, the Median of the Log of the processed Signals, StDev of the Log of the processed Signals, the %CV of the processed signals.

The Median Log Proc Signal, %CV, StDev of the Log of the processed signals all show up in the Agilent SpikeIns Signal Statistics table of the QC report.

For each sequence, use the calculated Background- SubtractedSignalAverage and compare against the StdDeviation of the Negative Controls (StdDevBgSubSigNegCtrl) using the formula BGSubAverage * MultErrorGreen > StdDevBgSubSigNegCtrl. Exclude the Proc Signals that fail this test, and use the median of the Proc Signals for the remaining sequences as the initial guess.

b Max is estimated as Log(Scanner SaturationValue).

c x0 is estimated by starting with the y- value (max+min)/2, then finding the 2 closest Med Log Proc Signals above and below this point. Finding the Log(concentrations) of those points and then computing a slope and an intercept by

slope = (MedianLogProcSig[HIGH] MedianLogProcSig[LOW])/(LogConc[HIGH] LogConc[LOW]); intercept = LogConc[HIGH] slope * MedianLogProcSig[HIGH]

d w is estimated by using the slope calculated above. By looking at the derivative of F(x) at x0 we get DF(x):x0 = (max- min)/4*w so w = 4*slope / (max min).

e After the estimates are complete the data is fit and the parameters (Min,Max, x0, w) are optimized by using a parameterized curve fitting routine (called

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Levenberg- Marquardt and is a standard technique documented in Numerical Recipes in C on pages 683 688).

f After the curve fitting is done, the Low Relative Concentration is calculated as x0 2.3*w.

g The High relative Concentration is calculated as x0 + 2.2*w.

h All the eQC points falling between x0 2.3*w and x0 + 2.2*w are then fit through a line with the Slope and R- Squared value reported.

i All of the points with a concentration below Low Concentration are used to calculate SpikeIn Detection limit. For each probe, the mean and standard deviation is calculated in linear BGSubSignal space. Then the average plus 1 standard deviation is calculated for each probe. The maximum of these is used. It is converted to log10 space and reported as the SpikeIn Detection Limit.

Relation of curve fit calculations to statistics in table In summary, Table 16 presents descriptions of the statistics in Figure 42, their definitions within the equation and their output in the stats table.

Table 16 Spike-In Concentration-Response Statistics for 1-color microarrays

Statistic Description Where in calculations Stats Table Output

Saturation Point upper limit of detection max-step b eQCOneColorLogHighSignal

Low Threshold lower limit of detection min-step a eQCOneColorLogLowSignal

Low Threshold Error error for lower limit See equation below table eQCOneColorLogLowSignalError

Low Signal lowest quantifiable signal in linear range

lowest signal from linear fit in step h

eQCOneColorLinFitLogLowSignal

High Signal highest quantifiable signal in linear range

highest signal from linear fit in step h

eQCOneColorLinFitLogHighSignal

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where the set A is from step a in the table

Low Relative Concentration lowest concentration leading to quantifiable signal

x0-2.3w in step f eQCOneColorLinFitLogLowConc

High Relative Concentration highest concentration leading to quantifiable signal

x0+2.2w in step g eQCOneColorLinFitLogHighConc

Slope slope of the linear fit on sigmoidal curve

from step h eQCOneColorLinFitSlope

R^2 Value correlation coefficient for linear fit

from step h eQCOneColorLinFitRSQ

SpikeIn Detection Limit The average plus 1 standard deviation of the spike ins below the linear concentration range

from step i eQCOneColorSpikeInDetectionLi mit

Table 16 Spike-In Concentration-Response Statistics for 1-color microarrays

Statistic Description Where in calculations Stats Table Output

LowThresholdError SD Log ProcessedSignals( ) 2

A =

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Accuracy of linear fit to middle of sigmoidal curve Agilent calculated the % difference between expected log processed signals at the high and low relative concentrations on the linear curve with the expected log signals for the same concentrations on the sigmoidal curve.

For the high end of the linear range, the % difference is 15.36%.

For the low end of the linear range, the % difference is 16.75%.

QC Report Results 2 QC Report Results in the FEPARAMS and Stats Tables

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QC Report Results in the FEPARAMS and Stats Tables

See Parameters/options (FEPARAMS) on page 129 and Statistical results (STATS) on page 160 of this guide for descriptions of the parameters and statistics listed in the tables.

The FEPARAMS table contains most of the QC header information. The Stats table output contains all the metrics shown on the QC Reports. These QC stats let you make tracking charts of individual metrics that you may want to follow over time. To separate out the FEPARAMS and Stats tables from each other and the FEATURES table, see the Feature Extraction 12.2 User Guide.

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QC Metric Set Results

The figures in this section show the metric names and default thresholds for the QC metric set results that appear in the Evaluation Tables for each of the QC metric sets available for Feature Extraction:

CGH_QCMT_Date

ChIP_QCMT_Date

GE1_QCMT_Date

GE2_QCMT_Date

miRNA_QCMT_Date

You can display the QC Metric Set Properties by double-clicking on a QC metric set in the QC Metric Set Browser.

where QCMT means QC Metrics with Thresholds, QCM means QC Metrics without thresholds, and Date is the date that the metric set was released from Agilent.

For details on the logic used for evaluating metrics, see Metric Evaluation Logic on page 125.

CGH_QCMT_Sep17

Figure 43 QC Metrics for CGH_QCMT_Sep17 metric set

QC Report Results 2 ChIP_QCMT_Jun14

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SNP probes are not used in calculation of any CGH QC Metric.

ChIP_QCMT_Jun14

Figure 44 QC Metrics for ChIP_QCMT_Jun14 metric set

GE1_QCMT_Jun14

Figure 45 QC Metrics for GE1_QCMT_Jun14 metric set

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GE2_QCMT_Dec17

Figure 46 QC Metrics for GE2_QCMT_Dec17 metric set

miRNA_QCMT_Jun14

Figure 47 QC Metrics for miRNA_QCMT_Jun14 metric set

QC Report Results 2 Metric Evaluation Logic

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Metric Evaluation Logic

For details on how to associate a QC metric set with a protocol, see the Feature Extraction User Guide.

When a QC metric set is associated with a protocol, it is used to evaluate results using up to three defined threshold values for given metrics. Results are then flagged in the QC Report Evaluation Metrics table according to the logic described in the following diagram and tables.

Figure 48 shows the metric evaluation using three threshold levels. The black dots indicate how a result is evaluated if its value is the same as a limit value.

Figure 48 Three-level QC Metrics evaluation used for Feature Extraction

The following tables describe how results are evaluated using up to three threshold levels.

Metric Evaluation Logic tables

In the following tables, evaluation metrics are described for 18 cases (IDs). Results are compared to four limit values, shown in the Limits used table: upper limit, upper warning limit, lower warning limit, and lower limit (v1 through v4). The logic used is described in the center table, showing the metric evaluation indication (Excellent, Good, Evaluate) that

Evaluate

Evaluate

Good

Good

Excellent

Upper limit

Lower limit

Upper warning limit

Lower warning limit

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is based on how the result compares to the given limit value(s). Cases covered indicate the type of threshold along with the boundaries that are displayed in the QC Report.

(value > Upper limit) => Evaluate

(value > Upper Warning limit) and (value <= Upper limit) => Good

(value >= Lower Warning limit) and (value <= Upper warning limit) => Excellent

(value >= Lower limit) and (value < Lower Warning limit) => Good

(value < Lower limit) => Evaluate

Figure 49 QC Metrics evaluation tables and cases

127Agilent Technologies

Agilent Feature Extraction 12.2 Reference Guide

3 Text File Parameters and Results

Parameters/options (FEPARAMS) 129

FULL FEPARAMS Table 129

COMPACT FEPARAMS Table 151

QC FEPARAMS Table 154

MINIMAL FEPARAMS Table 157

Statistical results (STATS) 160

STATS Table (ALL text output types) 160

Feature results (FEATURES) 179

FULL Features Table 179

COMPACT Features Table 190

QC Features Table 195

MINIMAL Features Table 201

Other text result file annotations 205

Feature Extraction produces a tab- delimited text file that contains three tables of input parameters and output results.

These tables are FEPARAMS, STATS, and FEATURES. These three tables list all the possible parameters, statistics and feature results that can be generated in the text output file.

FEPARAMS table Contains input parameters and options used to run Feature Extraction.

STATS table Gives results derived from statistical calculations that apply to all features on the microarray.

FEATURES table Displays results for each feature in over 90 output columns, such as gene name, log ratio, processed signal, mean signal, or dye- normalized signal.

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You have the option in the Project Properties sheet of selecting to generate either the FULL set of parameters, statistics and feature information, COMPACT, QC or MINIMAL. COMPACT output package is the default.

The COMPACT output package contains only those columns that are required by GeneSpring and DNA Analytics software. The tables on the following pages present the text file summary for all output package types (FULL, COMPACT, QC, or MINIMAL).

You also have the option to generate one file with all three tables or three separate files with one for each table. To select to generate one file or three, see the Feature Extraction 12.2 User Guide.

To display the text results file in an easy- to- read format, see the Feature Extraction 12.2 User Guide.

NOTE The parameters, statistical results, and feature results included vary for any one output file, depending on the application and protocol used for Feature Extraction.

Text File Parameters and Results 3 Parameters/options (FEPARAMS)

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Parameters/options (FEPARAMS)

The top- most section of the result file contains the parameters and option choices that you used to run Feature Extraction.

FULL FEPARAMS Table

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table)

Protocol Step Parameters Type/Options Description

Protocol _Name text Name of protocol used

Protocol_date text Date the protocol was last modified

Scan_date text Date the image was scanned

Scan_ScannerName text Serial number of the scanner used

Scan_NumChannels integer Number of channels in the scan image

Scan_MicronsPerPixelX float Number of microns per pixel in the X axis of the scan image

Scan_MicronsPerPixelY float Number of microns per pixel in the Y axis of the scan image

Scan_OriginalGUID text The global unique identifier for the scan image

Grid_Name text Grid template name or grid file name

Grid_Date integer Date the grid template or grid file was created

Grid_NumSubGridRows integer Number of subgrid columns

Grid_NumSubGridCols integer Number of subgrid columns

Grid_NumRows integer Number of spots per row of each subgrid

Grid_NumCols integer Number of spots per column of each subgrid

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Grid_RowSpacing float Space between rows on the grid

Grid_ColSpacing float Space between column on the grid

Grid_OffsetX float In a dense pack array, the offset in the X direction

Grid_OffsetY float In a dense pack array, the offset in the Y direction

Grid_NomSpotWidth float Nominal width in microns of a spot from grid

Grid_NomSpotHeight float Nominal height in microns of a spot from grid

Grid_GenomicBuild text The build of the genome used to create the annotation (if available). If the genome build is not available (not all designs have this information), then it is not put out. All recent and all future designs have it.

FeatureExtractor_Barcode text Barcode of the Agilent microarray read from the scan image

FeatureExtractor_Sample text Names of hybridized samples (red/green)

FeatureExtractor_ScanFileName text Name of the scan file used for Feature Extraction

FeatureExtractor_ArrayName text Microarray filename

FeatureExtractor_DesignFileName text Design or grid file used for Feature Extraction

FeatureExtractor_PrintingFileName text Print file (if available) used for Feature Extraction

FeatureExtractor_PatternName text Agilent pattern file name

FeatureExtractor_ExtractionTime text Time stamp at the beginning of Feature Extraction run for the extraction set

FeatureExtractor_UserName text Windows Log-In Name of the User who ran Feature Extraction

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

Text File Parameters and Results 3 FULL FEPARAMS Table

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FeatureExtractor_ComputerName text Computer name on which Feature Extraction was run

FeatureExtractor_ScanFileGUID text GUID of the scan file

FeatureExtractor_IsXDRExtraction integer

1 = True

0 = False

Indicates whether or not the extraction was an XDR extraction.

DyeNorm_NormFilename text Name of the dye normalization list file

DyeNorm_NormNumProbes integer Number of probes in the dye normalization list

Grid_IsGridFile boolean Indicates whether the grid is from a grid file.

Scan_NumScanPass 1 or 2 For 5 micron scans, indicates whether the scan mode was a single (1) or double-pass scan mode on the Agilent Scanner.

Place Grid GridPlacement_Version text Version of the grid placement algorithm

Place Grid GridPlacement_ArrayFormat integer Choices for grid placement based on the format of the image. Choices include:

Automatically Determine

Single Density (11k, 22k)

Double Density (44k)

95k

185 (5 and 10 uM)

65 micron (5 and 10 uM)

30 micron single pack

30 micron multi pack

244 (5 and 10 uM)

25k

Third Party

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

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Place Grid GridPlacement_enableOriginXCal integer

1 = True

0 = False

Indicates status of the Use the correlation method to obtain origin X of subgrids flag

Place Grid GridPlacement_enableUseCentralPack integer

1 = True

0 = False

Indicates status of the Use central part of pack for slope and skew calculation flag

Place Grid GridPlacement_placementMode integer

0

1

Mode of grid placement

Allow the grid to distort

Place the grid rigidly allowing only translation and rotation

Optimize Grid Fit IterativeSpotFind_CornerAdjust integer

0 = False

1 = True

Indicates whether or not the grid will be adjusted for better fit by looking at corner spots on the microarray

Optimize Grid Fit IterativeSpotFind_AdjustThreshold float Grid will be adjusted if absolute average difference between grid and spot positions is greater than this fraction

Optimize Grid Fit IterativeSpotFind_MaxIterations integer Maximum number of times spot finder algorithm is run to optimize the grid fit

Optimize Grid Fit IterativeSpotFind_FoundSpot Threshold

float Grid will be adjusted if this fraction or more of the features are considered found by the spot finder algorithm

Optimize Grid Fit IterativeSpotFind_NumCornerFeatures integer Indicates the square area of features in each corner of the microarray to be used to calculate the average difference

Find Spots SpotAnalysis_Version text Version of the spot analysis algorithm

Find Spots SpotAnalysis_weakthresh float Minimum difference between the average intensities of feature and background after Kmeans Initialization

Find Spots SpotAnalysis_MinimumNumPixels integer Minimum number of pixels required for the spot analysis

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

Text File Parameters and Results 3 FULL FEPARAMS Table

Feature Extraction Reference Guide 133

Find Spots SpotAnalysis_RegionOfInterest Multiplier

float Multiplier that defines how big the Region of Interest (ROI) is in terms of nominal spot spacing

Find Spots SpotAnalysis_convergence_factor float Convergence factor of KMeans algorithm

Find Spots SpotAnalysis_max_em_iter integer Maximum number of iterations of the Bayesian Classification

Find Spots SpotAnalysis_max_reject_ratio float Maximum fraction of pixels to be rejected while software performs spotfinding

Find Spots SpotAnalysis_kmeans_rad_reject_ factor

float Factor that defines how much individual spot size may vary relative to the nominal spot size

Find Spots SpotAnalysis_kmeans_cen_reject_ factor

float Factor that defines how far the actual centroid may move relative to its nominal grid position (in terms of nominal radius). In the protocol this parameter is called the Spot Deviation Limit.

Find Spots SpotAnalysis_kmeans_moi_reject_ factor

float Maximum allowable moment of inertia of the spot

Find Spots SpotAnalysis_isspot_factor float Factor from the statistics of the found feature and background that indicates if the spot is a spot.

Find Spots SpotAnalysis_isweakspot_factor float Factor from the statistics of the found feature and background that indicates if the spot is a strong one.

Find Spots SpotAnalysis_BackgroundThreshold float Factor by which the individual spot background may vary from the running average of all the background means.

Find Spots SpotAnalysis_ROIType integer Type of Region of Interest

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

134 Feature Extraction Reference Guide

3 Text File Parameters and Results FULL FEPARAMS Table

Find Spots SpotAnalysis_UseNominalDiameter FromGT

integer

1 = True

0 = False

If True, the nominal spot diameter from the grid template is used as a starting point for final spot diameter computation.

If False, the nominal diameter is obtained from the grid placement algorithm.

Find Spots SpotAnalysis_RejectMethod integer

0

2

3

Pixel Outlier Rejection turned off

Standard Deviation based

Interquartile Range based

Find Spots SpotAnalysis_StatBoundFeat float Multiplier parameters for feature outlier rejection method as selected above

Find Spots SpotAnalysis_StatBoundBG float Multiplier parameters for background outlier rejection method as selected above

Find Spots SpotAnalysis_SpotStatsMethod integer

1

2

Different algorithms to calculate spot statistics

CookieCutter method

Whole Spot method

Find Spots SpotAnalysis_CookiePercentage float The fraction of the nominal radius used to draw the cookie around the centroid of each spot

Find Spots SpotAnalysis_ExclusionZone Percentage

float The outer radius of the exclusion zone based on nominal spot size

Find Spots SpotAnalysis_EstimateLocalRadius integer

1 = True

0 = False

The option to calculate the outer radius of the local background based on row and column spacing

Find Spots SpotAnalysis_LocalBGRadius float The outer radius of the local background supplied from the protocol if EstimateLocalRadius is not selected

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

Text File Parameters and Results 3 FULL FEPARAMS Table

Feature Extraction Reference Guide 135

Find Spots SpotAnalysis_SignalMethod integer The option for the statistical method for determining signals from features: either mean (and standard deviation) or median (and normalized IQR).

Mean is 1 and Median is 2.

Find Spots SpotAnalysis_ComputePixelSkew integer

true = 1

false = 0

The option to set whether the program computes and shows the skew of each feature. Default is false.

Find Spots SpotAnalysis_PixelSkewCookiePct float (0.00-1.00; 0.70 default)

The percentage of the feature that should be used when calculating the pixel skew. A value of .70 means 70% of the radius of the feature.

Find Spots SpotAnalysis_CentroidDiff Integer

1 = True

0 = False

The software computes the per feature Centroid Difference between the Grid position and the Spot Center.

Find Spots SpotAnalysis_NozzleAdjust Integer

1 = True

0 = False

The software attempts to adjust a nozzle group in order to compensate for variations in printing.

Flag Outliers OutlierFlagger_Version text Version of Outlier Flagger algorithm

Flag Outliers OutlierFlagger_NonUnifOLOn integer

1 = True

0 = False

NonUniformity Outlier flagging turned on

NonUniformity Outlier flagging turned off

Flag Outliers OutlierFlagger_FeatATerm float Applies to feature: specifies the intensity dependent variance and is set to the square of the CV

Flag Outliers OutlierFlagger_FeatBTerm float Applies to feature: specifies the variance due to the Poisson distributed noise

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

136 Feature Extraction Reference Guide

3 Text File Parameters and Results FULL FEPARAMS Table

Flag Outliers OutlierFlagger_FeatCTerm float Applies to feature: specifies variance due to background noise of the scanner, slide glass, and other signal-independent sources

Flag Outliers OutlierFlagger_BGATerm float Applies to background: specifies the intensity-dependent variance and is set to the square of the CV

Flag Outliers OutlierFlagger_BGBTerm float Applies to background: specifies the variance due to the Poisson distributed noise

Flag Outliers OutlierFlagger_BGCTerm float Applies to background: specifies variance due to background noise of the scanner, slide glass, and other signal-independent sources

Flag Outliers OutlierFlagger_OLAutoComputeABC integer

1 = True

0 = False

AutoCompute Outlier flagging turned on

AutoCompute Outlier flagging turned off

For Agilent protocols when this flag is turned on, the polynomial is calculated automatically. This means that all above Feature and BG terms for B and C no longer appear in the output. Rather, they are calculated automatically and appear in the STATS table. Also, the eight parameters following this row appear.

Flag Outliers OutlierFlagger_FeatBCoeff float Feature: Red Poissonian Noise Term Multiplier

Flag Outliers OutlierFlagger_FeatCCoeff float Feature: Red Signal Constant Term Multiplier

Flag Outliers OutlierFlagger_FeatBCoeff2 float Feature: Green Poissonian Noise Term Multiplier

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

Text File Parameters and Results 3 FULL FEPARAMS Table

Feature Extraction Reference Guide 137

Flag Outliers OutlierFlagger_FeatCCoeff2 float Feature: Green Signal Constant Term Multiplier

Flag Outliers OutlierFlagger_BGBCoeff float Background: Red Poissonian Noise Term Multiplier

Flag Outliers OutlierFlagger_BGCCoeff float Background: Red Signal Constant Term Multiplier

Flag Outliers OutlierFlagger_BGBCoeff2 float Background: Green Poissonian Noise Term Multiplier

Flag Outliers OutlierFlagger_BGCCoeff2 float Background: Green Signal Constant Term Multiplier

Flag Outliers OutlierFlagger_PopnOLOn integer

1 = True

0 = False

Population Outlier flagging turned on

Population Outlier flagging turned off

Flag Outliers OutlierFlagger_MinPopulation integer Minimum number of replicates to turn on population outlier flagging

Flag Outliers OutlierFlagger_IQRatio float The boundary conditions for conducting box-plot analysis to isolate population outliers

Flag Outliers OutlierFlagger_BackgroundIQRatio float The boundary conditions for conducting box-plot analysis to isolate population outliers for the background

Flag Outliers OutlierFlagger_Use Qtest integer

1 = True

0 = False

Enables Qtest statistics when the minimum number of replicates for population outliers is greater than 2 and less than the minimum population specified in the outlier section of the protocol.

Flag Outliers OutlierFlagger_UsePopnOLInMAGE integer

1 = True

0 = False

Indicates whether to report population outliers as Failed in MAGEML output

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

138 Feature Extraction Reference Guide

3 Text File Parameters and Results FULL FEPARAMS Table

Compute Bkgd, Bias and Error

BGSubtractor_MultiplicativeDetrend On

integer

1 = True

0 = False

Enables multiplicative detrending.

1-color and CGH microarray protocols have this parameter enabled.

Compute Bkgd, Bias and Error

BGSubtractor_MultDetrendWinFilter integer

0

1

2

No filtering

Average filtering

Median filtering

Compute Bkgd, Bias and Error

BGSubtractor_MultDetrendIncrement integer The increment in number of features by which the square window is shifted horizontally and vertically on the microarray.

Compute Bkgd, Bias and Error

BGSubtractor_MultDetrendWindow integer Specifies size of the square window by the number of rows and columns. The specified percentage of low intensity features is selected from this window size.

Compute Bkgd, Bias and Error

BGSubtractor_MultDetrendNeighbor- hoodSize

float

[0-1]

Specifies the fraction of total number of neighborhood data points that will be weighted for linear regression during surface fitting for each data point

Compute Bkgd, Bias and Error

BGSubtractor_MultHighPassFilter integer

1 = True

0 = False

Enables rejection of probes close to

zero signal from the set of features used in the fit.

Compute Bkgd, Bias and Error

BGSubtractor_PolynomialMultipli- cativeDetrend

integer

1 = True

0 = False

The option to use a polynomial surface fit method for the multiplicative detrending fit (rather than LOESS).

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

Text File Parameters and Results 3 FULL FEPARAMS Table

Feature Extraction Reference Guide 139

Compute Bkgd, Bias and Error

BGSubtractor_NegCtrlThresholdMultD etrendFactor

float This factor multiplies the negative control spread to determine the threshold signal below which low intensity features are filtered out of the multiplicative detrending fit set.

Compute Bkgd, Bias and Error

BGSubtractor_PolynomialMulti- plicativeDetrendDegree

integer

[-1, 5]

Shows the degree of the polynomial fit used for the multiplicative detrending. The most common choices are 2 (quadratic or 2nd order surface) and 4 (4th order surface).

Compute Bkgd, Bias and Error

BGSubtractor_TestMultDetrendOnCVs integer Tests whether the replicate CVs improve (i.e. decrease) after multiplicative detrending. If this choice is 1=True, and the replicate CVs don't improve, Feature Extraction doesn't use the multiplicative detrending for that array.

Compute Bkgd, Bias and Error

BGSubtractor_MultDetrendOn Replicates

integer

1 = True

0 = False

Specifies to use only replicated probes (with multiple features) normalized to their replicate average for the multiplicative detrending set.

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

140 Feature Extraction Reference Guide

3 Text File Parameters and Results FULL FEPARAMS Table

Compute Bkgd, Bias and Error

BGSubtractor_BGSubMethod integer

1

2

3

5

6

7

Either minimum feature or minimum local background across the microarray for background subtraction (global method)

Average of local backgrounds for background subtraction (global method)

Average of negative controls for background for background subtraction (global method)

Local background corresponding to each feature for background subtraction (local method)

Minimum feature across the microarray for background subtraction (global method)

No background subtraction

Compute Bkgd, Bias and Error

BGSubtractor_MaxPVal float The pValue at which a feature is determined to be statistically significant above background

Compute Bkgd, Bias and Error

BGSubtractor_WellAboveMulti float The number of standard deviations above background at which the feature is flagged as well above background

Compute Bkgd, Bias and Error

BGSubtractor_BackgroundCorrectionO n

integer

1 = True

0 = False

Globally adjust background turned on

Globally adjust background turned off

Compute Bkgd, Bias and Error

BGSubtractor_BgCorrectionOffset Adjust the signal of all features by an offset constant so that very low signal features end up at this offset. Appears when Globally adjust background is turned on.

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

Text File Parameters and Results 3 FULL FEPARAMS Table

Feature Extraction Reference Guide 141

Compute Bkgd, Bias and Error

BGSubtractor_CalculateSurface MetricsOn

integer

1 = True

0 = False

Surface fit is done and metrics calculated.

Surface fit and metrics are not done.

Compute Bkgd, Bias and Error

BGSubtractor_SpatialDetrendOn integer

1 = True

0 = False

Spatial detrend turned on

Spatial detrend turned off

Compute Bkgd, Bias and Error

BGSubtractor_DetrendLowPassFilter integer

1 = True

0 = False

Low pass filter used

Low pass filter not used

Compute Bkgd, Bias and Error

BGSubtractor_DetrendLowPass Percentage

integer Specifies percentage of features based on the lowest intensity probes in each window that will be used to fit the surface

Compute Bkgd, Bias and Error

BGSubtractor_DetrendLowPass Window

integer Specifies size of the square window by the number of rows and columns. The specified percentage of low intensity features is selected from this window size.

Compute Bkgd, Bias and Error

BGSubtractor_DetrendLowPass Increment

integer The increment in number of features by which the above window is shifted horizontally and vertically on the microarray

Compute Bkgd, Bias and Error

BGSubtractor_NegCtrlSpreadCoeff float The number of multiples of the negative control spread that defines the signal range within which features are considered to be within the negative control range for FeaturesInNegativeControlRange background detrend option.

Compute Bkgd, Bias and Error

BGSubtractor_NegCtrlSpreadRobust On

float Specifies to remove negative control features that are outliers before calculating the negative control spread for use with FeaturesInNegativeControlRange.

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

142 Feature Extraction Reference Guide

3 Text File Parameters and Results FULL FEPARAMS Table

Compute Bkgd, Bias and Error

BGSubtractor_AdditiveDetrend FeatureSet

integer

0

1

2

Determines which features are considered for the surface fit set

All inlier features

Negative control inliers only

Features in negative control range

Compute Bkgd, Bias and Error

BGSubtractor_DetrendNeighborhood Size

float Specifies the fraction of total number of neighborhood data points that will be weighted for linear regression during surface fitting for each data point

Compute Bkgd, Bias and Error

BGSubtractor_ErrModelSignificance integer

0 = pixel statistics

1 = error model

Decides whether the error model or pixel staistics are used to determine Positive and Significance calls and WellAboveBackground.

Compute Bkgd, Bias and Error

BGSubtractor_RobustNCStats integer

1 = True

0 = False

Specifies if a variation in the population algorithm is turned on. This algorithm repeats the population outlier IQR algorithm on all features classified as negative controls, after the first pass of population algorithm has been run on each sequence.

You may want to use this algorithm when you see hot features that have not been flagged as population outliers or hot sequences where all features of the sequence have higher signals than those in other negative control sequences.

Compute Bkgd, Bias and Error

BGSubtractor_RobustNCOutlierFactor float To calculate robust IQR statistics, the algorithm uses upper and lower limits that contain a (Multiplier x IQR) term. This parameter is the Multiplier.

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

Text File Parameters and Results 3 FULL FEPARAMS Table

Feature Extraction Reference Guide 143

Compute Bkgd, Bias and Error

BGSubtractor_ErrorModel integer

2

0

Choose universal error, or the most conservative

Universal Error Model

Most Conservative

Compute Bkgd, Bias and Error

BGSubtractor_MultErrorGreen float Multiplicative error component in Green channel

Compute Bkgd, Bias and Error

BGSubtractor_MultErrorRed float Multiplicative error component in Red channel

Compute Bkgd, Bias and Error

BGSubtractor_AutoEstimateAddErrorG reen

integer

1 = True

0 = False

Auto-estimation turned on

Auto-estimation turned off

Compute Bkgd, Bias and Error

BGSubtractor_AutoEstimateAddErrorR ed

integer

1 = True

0 = False

Auto-estimation turned on

Auto-estimation turned off

Compute Bkgd, Bias and Error

BGSubtractor_AddErrorGreen float This additive error component in the green channel is entered in the protocol when auto-estimation is turned off. When auto-estimation is turned on, the estimated error value appears in the Stats table as AddErrorEstimateGreen.

Compute Bkgd, Bias and Error

BGSubtractor_AddErrorRed float This additive error component in the red channel is entered in the protocol when auto-estimation is turned off. When auto-estimation is turned on, the estimated error value appears in the Stats table as AddErrorEstimateRed.

Compute Bkgd, Bias and Error

BGSubtractor_MultNcAutoEstimate float

[0-10]

Multiplier for the first term (standard deviation of the inlier negative control) in the additive error equation.

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

144 Feature Extraction Reference Guide

3 Text File Parameters and Results FULL FEPARAMS Table

Compute Bkgd, Bias and Error

BGSubtractor_MultRMSAutoEstimate float

[0-10]

Multiplier for the second term (gMultSpatialDetrendRMSFit) in the additive error equation.

Compute Bkgd, Bias and Error

BGSubtractor_MultResidualsRMSAuto Estimate

float

[0-10]

Multiplier for the third term in the additive error equation.

Compute Bkgd, Bias and Error

BGSubtractor_AutoEstimateNCOnly Thresh

float This parameter is for single density 8-pack microarrays where Feature Extraction may not be able to accurately subtract the background using the spatial detrending method. This parameter provides a minimum number of features needed for the software to use the residual or the RMS to estimate the additive error. It comes up only if using low density 8-pack microarrays.

Compute Bkgd, Bias and Error

BGSubtractor_UseSurrogates integer

1 = True

0 = False

Flag indicating the use of surrogates

Use of surrogates turned on

Use of surrogates turned off

Compute Bkgd, Bias and Error

BGSubtractor_Version text Version of BGSubtractor algorithm

Correct Dye Biases DyeNorm_Version text Version of DyeNorm algorithm

Correct Dye Biases DyeNorm_UseDyeNormList integer

0

1

2

Automatically determine

True

False

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

Text File Parameters and Results 3 FULL FEPARAMS Table

Feature Extraction Reference Guide 145

Correct Dye Biases DyeNorm_SelectMethod integer

4

5

6

7

Method for selecting features used for measurement of dye bias:

Use All Probes

Use List of Normalization Genes

Use Rank Consistent Probes

Use Rank Consistent List of Normalization Genes

Correct Dye Biases DyeNorm_ArePosNegCtrlsOK integer

1 = True

0 = False

Use positive and negative controls for dye normalization.

Do not use these controls.

Correct Dye Biases DyeNorm_SignalCharacteristics integer

1

2

3

Only positive and significant signals

All positive signals

All negative and positive signals

Correct Dye Biases DyeNorm_CorrMethod integer

0

1

2

Methods for computation of dye normalization factor to remove dye bias

Linear

Linear&LOWESS (locally weighted linear regression preceded by linear scaling in each dye channel)

LOWESS (locally weighted linear regression)

Correct Dye Biases DyeNorm_LOWESSSmoothFactor float Smoothing parameter (Neighborhood size) for LOWESS curve fitting

Correct Dye Biases DyeNorm_LOWESSNumSteps integer Number of iterations in LOWESS

Correct Dye Biases DyeNorm_RankTolerance float The threshold to pick rank consistent features between 2 channels for measuring dye biases

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

146 Feature Extraction Reference Guide

3 Text File Parameters and Results FULL FEPARAMS Table

Correct Dye Biases DyeNorm_VariableRankTolerance integer

1 = True

0 = False

Allows the rank tolerance to vary with signal level to allow a fixed percentage of the data to be considered rank consistent.

Correct Dye Biases DyeNorm_MaxRankedSize integer The limit on the number of points used for the dye normalization set. If the number is greater than this, a random subset is chosen using this number of points.

Correct Dye Biases DyeNorm_IsBGPopnOLOn integer

1 = True

0 = False

Software excludes any features from the dye normalization set if the local backgrounds associated with those features have been flagged as population outliers (in either channel).

The default recommendation is False.

Compute Ratios Ratio_Version text Version of Ratio algorithm

Compute Ratios Ratio_PegLogRatioValue float Both positive and negative log ratio values are capped to this absolute value

miRNA Analysis miRNA_Analysis_OutputGeneView integer

1 = True

0 = False

Output Geneview File

Dont output Geneview File

miRNA Analysis miRNA_Analysis_EffectiveFeatSizeOn integer

1 = True

0 = False

Enable to analyze by effective feature size.

Disable analysis by effective feature size.

miRNA Analysis miRNA_Analysis_MaxFeatToCompEffe ctiveFeatSize

integer Maximum number of features

miRNA Analysis miRNA_Analysis_MinNumRatiosToCo mpEffectiveFeatSize

integer Maximum number of ratios

miRNA Analysis miRNA_Analysis_LowSigPctileToComp EffectiveFeatSize

float Low Signal Percentile

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

Text File Parameters and Results 3 FULL FEPARAMS Table

Feature Extraction Reference Guide 147

miRNA Analysis miRNA_Analysis_HighSigPctileToCom pEffectiveFeatSize

float High Signal Percentile

miRNA Analysis miRNA-Analysis_HighRatioCutOff float Throw away ratios greater than this value

miRNA Analysis miRNA_Analysis_DefEffectiveFeatSize Frac

float

miRNA Analysis miRNA_Analysis_MinNoiseMultToCo mpEffectiveFeatSize

float Minimum Noise Multiplier

miRNA Analysis miRNA_Analysis_IsDetectedMulti float Configures the IsProbeDetected Multiplier in the miRNA algorithm

miRNA Analysis miRNA_Analysis_MinimumTotalGeneS ignal

float Configures the Default Total Gene Signal if all probes are not detected. Used if the non detected probes are excluded from the calculation.

miRNA Analysis miRNA_Analysis_ExcludeNonDetecte dProbes

integer

1 = True

0 = False

Changes how the Total Gene Signal is calculated. If a Total Probe Signal is not detected, then it is not added to the Total Gene Signal. If a probe that is associated with an miRNA isnt detected because it fails its IsProbeDetected flag then, if this option is true, it will not contribute to the totalGeneSignal and its error will not propagate to the totalGeneError.

Exclude non detected probes from analysis

Include non detected probes in analysis (Results will be same as Feature Extraction v10.5)

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

148 Feature Extraction Reference Guide

3 Text File Parameters and Results FULL FEPARAMS Table

miRNA Analysis miRNA_Analysis_PropagateTotalGene SignalError

integer

1 = True

0 = False

Use this if and only if the all the probes are not detected and the non detected probes are excluded from the calculation (see option above). If true, Total Gene Signal Error is calculated as if all probes were included. Invalidates Default Total Gene Signal.

Calculate Metrics QCMetrics_UseSpikeIns integer

1 = True

0 = False

Use SpikeIns

Do not use SpikeIns

Calculate Metrics QCMetrics_minReplicatePopulation integer Minimum number of replicates necessary to calculate replicate statistics

Calculate Metrics QCMetrics_differentialExpression PValue

float The pValue to use to look for differentially expressed genes

Calculate Metrics QCMetrics_MaxEdgeDefect Threshold

float Maximum allowable fraction of features along any edge of the microarray that are non-uniform before a grid placement warning is given.

Calculate Metrics QCMetrics_MaxEdgeNotFound Threshold

float Maximum allowable fraction of features along any edge of the microarray that are not found before a grid placement warning is given.

Calculate Metrics QCMetrics_MaxLocalBGNonUnif Threshold

float Maximum allowable fraction of the local background regions on the microarray that are flagged as NonUniform before a grid placement warning is given.

Calculate Metrics QCMetrics_MinNegCtrlSDev float Minimum value for the standard deviation for the negative controls

Calculate Metrics QCMetrics_MinReproducibility float Minimum value for the reproducibility

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

Text File Parameters and Results 3 FULL FEPARAMS Table

Feature Extraction Reference Guide 149

Calculate Metrics QCMetrics_Formulation integer

1 = TwoColor

2 = OneColor

3 = CGH

The SpikeIn formulation to use for the SpikeIn Calculation. Different formulations will yield different expected values and different concentration values.

Calculate Metrics QCMetrics_EnableDyeFlip integer

1 = True

2 = False

If True (default), the sign of the slope for the spikeIns plot and its trend will be changed when the slope is detected to have the wrong sign. This means the labelling was intentionally flipped and must be flipped back.

Calculate Metrics QCMetrics_PercentileValuefor Signal float The PercentileIntensitySignal is calculated by the software on the [r,g]ProcessedSignal showing the signal at a given percentile over the NonControl features. This parameter is the percentile used for the calculation. By default the value is set to 75; the software generates the 75% Signal value of the ProcessedSignals for all channels available.

FeatureExtractor_Version text Version of Feature Extractor

FeatureExtractor_SingleTextFile Output

integer

1 = True

0 = False

The system prints the three tables (FEParams, Stats and Features) are printed in the same text file.

The system prints each of the three tables in separate text files.

FeatureExtractor_JPEGDownSample Factor

float Factor by which the image is scaled down and then converted to the JPEG format. Must be at least 2; 1 is no longer allowed.

FeatureExtractor_ColorMode integer

0

1

2

A flag to indicate output color

One color; green only

2-color

One color: red only

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

150 Feature Extraction Reference Guide

3 Text File Parameters and Results FULL FEPARAMS Table

FeatureExtractor_QCReportType integer

0

1

2

4

Type of QC report to generate

Gene Expression

CGH_ChIP

miRNA

Streamlined CGH

FeatureExtractor_OutputQCReport GraphText

integer

1 = True

0 = False

Generate output details on QC report graphs

Table 17 List of parameters and options contained within the FULL text output file (FEPARAMS table) (continued)

Protocol Step Parameters Type/Options Description

Text File Parameters and Results 3 COMPACT FEPARAMS Table

Feature Extraction Reference Guide 151

COMPACT FEPARAMS Table

Table 18 List of parameters and options contained within the COMPACT text output file (FEPARAMS table)

Protocol Step Parameters Type/Options Description

Protocol _Name text Name of protocol used

Protocol_date text Date the protocol was last modified

Scan_ScannerName text Agilent scanner serial number used

Scan_NumChannels integer Number of channels in the scan image

Scan_date text Date the image was scanned

Scan_MicronsPerPixelX float Number of microns per pixel in the X axis of the scan image

Scan_MicronsPerPixelY float Number of microns per pixel in the Y axis of the scan image

Scan_OriginalGUID text The global unique identifier for the scan image

Scan_NumScanPass 1 or 2 For 5 micron scans, indicates whether the scan mode was a single (1) or double-pass scan mode on the Agilent Scanner.

Grid_Name text Grid template name or grid file name

Grid_Date integer Date the grid template or grid file was created

Grid_NumSubGridRows integer Number of subgrid columns

Grid_NumSubGridCols integer Number of subgrid columns

Grid_NumRows integer Number of spots per row of each subgrid

Grid_NumCols integer Number of spots per column of each subgrid

Grid_RowSpacing float Space between rows on the grid

Grid_ColSpacing float Space between column on the grid

Grid_OffsetX float In a dense pack array, the offset in the X direction

152 Feature Extraction Reference Guide

3 Text File Parameters and Results COMPACT FEPARAMS Table

Grid_OffsetY float In a dense pack array, the offset in the Y direction

Grid_NomSpotWidth float Nominal width in microns of a spot from grid

Grid_NomSpotHeight float Nominal height in microns of a spot from grid

Grid_GenomicBuild text The build of the genome used to create the annotation (if available). If the genome build is not available (not all designs have this information), then it is not put out. All recent and all future designs have it.

FeatureExtractor_Barcode text Barcode of the Agilent microarray read from the scan image

FeatureExtractor_Sample text Names of hybridized samples (red/green)

FeatureExtractor_ScanFileName text Name of the scan file used for Feature Extraction

FeatureExtractor_ArrayName text Microarray filename

FeatureExtractor_ScanFileGUID text GUID of the scan file

FeatureExtractor_DesignFileName text Design or grid file used for Feature Extraction

FeatureExtractor_ExtractionTime text Time stamp at the beginning of Feature Extraction

FeatureExtractor_UserName text Windows Log-In Name of the User who ran Feature Extraction

FeatureExtractor_ComputerName text Computer name on which Feature Extraction was run

FeatureExtractor_Version text Version of Feature Extractor

FeatureExtractor_IsXDRExtraction integer

1 = True

0 = False

Says if result is from an XDR extraction

Table 18 List of parameters and options contained within the COMPACT text output file (FEPARAMS table)

Protocol Step Parameters Type/Options Description

Text File Parameters and Results 3 COMPACT FEPARAMS Table

Feature Extraction Reference Guide 153

FeatureExtractor_ColorMode integer

0

1

A flag to indicate output color

One color; green only

2-color

FeatureExtractor_QCReportType integer

0

1

2

4

Type of QC report to generate

Gene Expression

CGH_ChIP

miRNA

Streamlined CGH

DyeNorm_NormFilename text Name of the dye normalization list file

DyeNorm_NormNumProbes integer Number of probes in the dye normalization list

Grid_IsGridFile boolean

Table 18 List of parameters and options contained within the COMPACT text output file (FEPARAMS table)

Protocol Step Parameters Type/Options Description

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QC FEPARAMS Table

Table 19 List of parameters and options contained within the QC text output file (FEPARAMS table)

Protocol Step Parameters Type/Options Description

Protocol _Name text Name of protocol used

Protocol_date text Date the protocol was last modified

Scan_ScannerName text Agilent scanner serial number used

Scan_NumChannels integer Number of channels in the scan image

Scan_date text Date the image was scanned

Scan_MicronsPerPixelX float Number of microns per pixel in the X axis of the scan image

Scan_MicronsPerPixelY float Number of microns per pixel in the Y axis of the scan image

Scan_OriginalGUID text The global unique identifier for the scan image

Scan_NumScanPass 1 or 2 For 5 micron scans, indicates whether the scan mode was a single (1) or double-pass scan mode on the Agilent Scanner.

Grid_Name text Grid template name or grid file name

Grid_Date integer Date the grid template or grid file was created

Grid_NumSubGridRows integer Number of subgrid columns

Grid_NumSubGridCols integer Number of subgrid columns

Grid_NumRows integer Number of spots per row of each subgrid

Grid_NumCols integer Number of spots per column of each subgrid

Grid_RowSpacing float Space between rows on the grid

Grid_ColSpacing float Space between column on the grid

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Feature Extraction Reference Guide 155

Grid_OffsetX float In a dense pack array, the offset in the X direction

Grid_OffsetY float In a dense pack array, the offset in the Y direction

Grid_NomSpotWidth float Nominal width in microns of a spot from grid

Grid_NomSpotHeight float Nominal height in microns of a spot from grid

Grid_GenomicBuild text The build of the genome used to create the annotation (if available). If the genome build is not available (not all designs have this information), then it is not put out. All recent and all future designs have it.

FeatureExtractor_Barcode text Barcode of the Agilent microarray read from the scan image

FeatureExtractor_Sample text Names of hybridized samples (red/green)

FeatureExtractor_ScanFileName text Name of the scan file used for Feature Extraction

FeatureExtractor_ArrayName text Microarray filename

FeatureExtractor_ScanFileGUID text GUID of the scan file

FeatureExtractor_DesignFileName text Design or grid file used for Feature Extraction

FeatureExtractor_ExtractionTime text Time stamp at the beginning of Feature Extraction

FeatureExtractor_UserName text Windows Log-In Name of the User who ran Feature Extraction

FeatureExtractor_ComputerName text Computer name on which Feature Extraction was run

FeatureExtractor_Version text Version of Feature Extractor

FeatureExtractor_IsXDRExtraction integer

1 = True

0 = False

Says if result is from an XDR extraction

Protocol Step Parameters Type/Options Description

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FeatureExtractor_ColorMode integer

0

1

A flag to indicate output color

One color; green only

2-color

FeatureExtractor_QCReportType integer

0

1

2

4

Type of QC report to generate

Gene Expression

CGH_ChIP

miRNA

Streamlined CGH

DyeNorm_NormFilename text Name of the dye normalization list file

DyeNorm_NormNumProbes integer Number of probes in the dye normalization list

Grid_IsGridFile boolean Indicates whether the grid is from a grid file.

Protocol Step Parameters Type/Options Description

Text File Parameters and Results 3 MINIMAL FEPARAMS Table

Feature Extraction Reference Guide 157

MINIMAL FEPARAMS Table

Table 20 List of parameters and options contained within the MINIMAL text output file (FEPARAMS table)

Protocol Step Parameters Type/Options Description

Protocol _Name text Name of protocol used

Protocol_date text Date the protocol was last modified

Scan_ScannerName text Agilent scanner serial number used

Scan_NumChannels integer Number of channels in the scan image

Scan_date text Date the image was scanned

Scan_MicronsPerPixelX float Number of microns per pixel in the X axis of the scan image

Scan_MicronsPerPixelY float Number of microns per pixel in the Y axis of the scan image

Scan_OriginalGUID text The global unique identifier for the scan image

Scan_NumScanPass 1 or 2 For 5 micron scans, indicates whether the scan mode was a single (1) or double-pass scan mode on the Agilent Scanner.

Grid_Name text Grid template name or grid file name

Grid_Date integer Date the grid template or grid file was created

Grid_NumSubGridRows integer Number of subgrid columns

Grid_NumSubGridCols integer Number of subgrid columns

Grid_NumRows integer Number of spots per row of each subgrid

Grid_NumCols integer Number of spots per column of each subgrid

Grid_RowSpacing float Space between rows on the grid

Grid_ColSpacing float Space between column on the grid

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Grid_OffsetX float In a dense pack array, the offset in the X direction

Grid_OffsetY float In a dense pack array, the offset in the Y direction

Grid_NomSpotWidth float Nominal width in microns of a spot from grid

Grid_NomSpotHeight float Nominal height in microns of a spot from grid

Grid_GenomicBuild text The build of the genome used to create the annotation (if available). If the genome build is not available (not all designs have this information), then it is not put out. All recent and all future designs have it.

FeatureExtractor_Barcode text Barcode of the Agilent microarray read from the scan image

FeatureExtractor_Sample text Names of hybridized samples (red/green)

FeatureExtractor_ScanFileName text Name of the scan file used for Feature Extraction

FeatureExtractor_ArrayName text Microarray filename

FeatureExtractor_ScanFileGUID text GUID of the scan file

FeatureExtractor_DesignFileName text Design or grid file used for Feature Extraction

FeatureExtractor_ExtractionTime text Time stamp at the beginning of Feature Extraction

FeatureExtractor_UserName text Windows Log-In Name of the User who ran Feature Extraction

FeatureExtractor_ComputerName text Computer name on which Feature Extraction was run

FeatureExtractor_Version text Version of Feature Extractor

FeatureExtractor_IsXDRExtraction integer

1 = True

0 = False

Says if result is from an XDR extraction

Protocol Step Parameters Type/Options Description

Text File Parameters and Results 3 MINIMAL FEPARAMS Table

Feature Extraction Reference Guide 159

FeatureExtractor_ColorMode integer

0

1

A flag to indicate output color

One color; green only

2-color

FeatureExtractor_QCReportType integer

0

1

2

4

Type of QC report to generate

Gene Expression

CGH_ChIP

miRNA

Streamlined CGH

DyeNorm_NormFilename text Name of the dye normalization list file

DyeNorm_NormNumProbes integer Number of probes in the dye normalization list

Grid_IsGridFile boolean

Protocol Step Parameters Type/Options Description

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Statistical results (STATS)

This middle section of the text file describes the results from the global array- wide statistical calculations. The STATS results are reported to 9 decimal places in exponential notation for all results files (FULL, COMPACT, QC, or MINIMAL).

STATS Table (ALL text output types)

Table 21 Stats results contained in the text output file (STATS table)*

Stats (Green Channel) Stats (Red Channel) Type Description

gDarkOffsetAverage rDarkOffsetAverage float Average dark offset per image per channel as measured by scanner

gDarkOffsetMedian rDarkOffsetMedian float Median dark offset per image per channel as measured by the scanner

gDarkOffsetStdDev rDarkOffsetStdDev float Standard deviation of the data points measured by the scanner to determine the dark offset per image per channel.

gDarkOffsetNumPts rDarkOffsetNumPts integer Number of points of data measured by the scanner to determine the dark offset per image per channel

gSaturationValue rSaturationValue integer Signal intensity at which spot is considered saturated.

gAvgSig2BkgeQC rAvgSig2BkgeQC float The average ratio of net signal to local background for all spike-in probes

gAvgSig2BkgNegCtrl rAvgSig2BkgNegCtrl float The average ratio of net signal to local background for all negative control probes

gRatioSig2BkgeQC_NegCtrl rRatioSig2BkgeQC_NegCtrl float The ratio of AvgSig2BkgeQC to AvgSig2BkgNegCtrl

gNumSatFeat rNumSatFeat integer The number of saturated features on the microarray per channel

Text File Parameters and Results 3 STATS Table (ALL text output types)

Feature Extraction Reference Guide 161

gLocalBGInlierNetAve rLocalBGInlierNetAve float The average of the net signal of all inlier local backgrounds

gLocalBGInlierAve rLocalBGInlierAve float The average of all inlier local backgrounds

gLocalBGInlierSDev rLocalBGInlierSDev float The standard deviation of all inlier local backgrounds

gLocalBGInlierNum rLocalBGInlierNum integer The number of inlier local backgrounds

gGlobalBGInlierAve rGlobalBGInlierAve float The average of all inliers used in background estimation for the selected global background subtraction method or the average of all inlier local backgrounds if the local background subtraction method is selected (after global background adjustment is applied, if selected)

gGlobalBGInlierSDev rGlobalBGInlierSDev float The standard deviation of all inliers used in background estimation for the selected global background subtraction method or the standard deviation of all inlier local backgrounds if the local background subtraction method is selected

gGlobalBGInlierNum rGlobalBGInlierNum integer The number of all inliers used in background estimation for the selected global background subtraction method or the number of all inlier local backgrounds if the local background subtraction method is selected

gNumFeatureNonUnifOL rNumFeatureNonUnifOL integer The number of features that are flagged as non-uniformity outliers

gNumPopnOL rNumPopnOL integer The number of features that are flagged as population outliers

gNumNonUnifBGOL rNumNonUnifBGOL integer The number of local background regions that are flagged as non-uniformity outliers

gNumPopnBGOL rNumPopnBGOL integer The number of local background regions that are flagged as population outliers

gOffsetUsed rOffsetUsed float Software estimated scanner offset

Table 21 Stats results contained in the text output file (STATS table)* (continued)

Stats (Green Channel) Stats (Red Channel) Type Description

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3 Text File Parameters and Results STATS Table (ALL text output types)

gGlobalFeatInlierAve rGlobalFeatInlierAve float Average of all inlier features

gGlobalFeatInlierSDev rGlobalFeatInlierSDev float Standard deviation of all inlier features

gGlobalFeatInlierNum rGlobalFeatInlierNum float Number of all inlier features

AllColorPrcntSat float The percentage of features that are saturated in both the green AND red channels

AnyColorPrcntSat float The percentage of features that are saturated in either the green or red channel

AnyColorPrcntFeatNonUnifOL float The percentage of features that are feature non-uniformity outliers in either channel

AnyColorPrcntBGNonUnifOL float The percentage of local backgrounds that are non-uniformity outliers in either channel

AnyColorPrcntFeatPopnOL float The percentage of features that are population outliers in either the green or red channel

AnyColorPrcntBGPopnOL float The percentage of local backgrounds that are population outliers in either channel

TotalPrcntFeatOL float The percentage of non-control features that are feature non-uniformity outliers in either the green or red channel or are saturated in both channels

gBGAdjust rBGAdjust float Background offset constant to adjust all feature signals. If Adjust Background Globally is set True, all feature signals are adjusted by this offset. If set to the value entered in the protocol, all feature signals are adjusted so that very low level feature signals equal the protocol value.

gNumNegBGSubFeat rNumNegBGSubFeat integer Number of background-subtracted features with negative signals

Table 21 Stats results contained in the text output file (STATS table)* (continued)

Stats (Green Channel) Stats (Red Channel) Type Description

Text File Parameters and Results 3 STATS Table (ALL text output types)

Feature Extraction Reference Guide 163

gNonCtrlNumNegFeatBGSub Sig

rNonCtrlNumNegFeatBGSubSig integer Number of non-control features with negative background-subtracted signals

gLinearDyeNormFactor rLinearDyeNormFactor float Global dye norm factor

gRMSLowessDNF rRMSLowessDNF float The root mean square of the average lowess dye norm factor. The lowess dye norm factor for each feature is its DyeNormSignal divided by its BGSubSignal.

DyeNormDimensionlessRMS float Dimensionless RMS correction metric (metric that indicates how much correction has been applied based upon the LOWESS curve)

DyeNormUnitWeightedRMS float Unit weighted RMS correction metric (metric that indicates how much correction has been applied based upon the LOWESS curve)

gSpatialDetrendRMSFit rSpatialDetrendRMSFit float Root mean square (RMS) of the fitted data points obtained from the Loess algorithm. This gives an idea of the curvature of the surface fit.

gSpatialDetrendRMS Filtered MinusFit

rSpatialDetrendRMS Filtered MinusFit

float Approximate residual from the surface fit.

gSpatialDetrendSurfaceArea rSpatialDetrendSurfaceArea float Normalized areathe fitted surface area divided by the projected area on the microarray; also gives an idea of the curvature of the surface gradient.

gSpatialDetrendVolume rSpatialDetrendVolume float Sum of the intensities of the surface area minus the offset. The offset is calculated as the volume under the flat surface (parallel to the glass slide) passing through the minimum intensity point of the fitted surface. This number (total volume - offset) is normalized by the area of the microarray.

gSpatialDetrendAveFit rSpatialDetrendAveFit float Describes the average intensity of the surface gradient

Table 21 Stats results contained in the text output file (STATS table)* (continued)

Stats (Green Channel) Stats (Red Channel) Type Description

164 Feature Extraction Reference Guide

3 Text File Parameters and Results STATS Table (ALL text output types)

gNonCtrlNumSatFeat rNonCtrlNumSatFeat integer The number of saturated non-control features

gNonCtrl99PrcntNetSig rNonCtrl99PrcntNetSig float NetSignal intensity at 99th percentile for all non-control probes

gNonCtrl50PrcntNetSig rNonCtrl50PrcntNetSig float NetSignal intensity at 50th percentile for all non-control probes

gNonCtrl1PrcntNetSig rNonCtrl1PrcntNetSig float NetSignal intensity at 1st percentile for all non-control probes

gNonCtrlMedPrcntCVBGSub Sig

rNonCtrlMedPrcntCVBGSubSig float The median percent CV of background-subtracted signals for inlier noncontrol probes

gCtrleQCNumSatFeat rCtrleQCNumSatFeat integer The number of saturated spike-in features

gCtrleQC99PrcntNetSig rCtrleQC99PrcntNetSig float NetSignal intensity at 99th percentile of all spike-in probes

gCtrleQC50PrcntNetSig rCtrleQC50PrcntNetSig float NetSignal intensity at 50th percentile of all spike-in probes

gCtrleQC1PrcntNetSig rCtrleQC1PrcntNetSig float NetSignal intensity at 1st percentile of all spike-in probes

geQCMedPrcntCVBGSubSig reQCMedPrcntCVBGSubSig float The median percent CV of background-subtracted signals for inlier spike-in probes

geQCSig2BkgLow1 reQCSig2BkgLow1 float Median ratio (net signal to BGUsed) of all inlier features for an spike-in probe with lowest concentration spiked in red and green channels

geQCSig2BkgLow2 reQCSig2BkgLow2 float Median ratio (net signal to BGUsed) of all inlier features for an spike-in probe with second lowest concentration spiked in red and green channels

gNegCtrlNumInliers rNegCtrlNumInliers integer Number of all inlier negative controls

Table 21 Stats results contained in the text output file (STATS table)* (continued)

Stats (Green Channel) Stats (Red Channel) Type Description

Text File Parameters and Results 3 STATS Table (ALL text output types)

Feature Extraction Reference Guide 165

gNegCtrlAveNetSig rNegCtrlAveNetSig float Average net signal of all inlier negative controls

gNegCtrlSDevNetSig rNegCtrlSDevNetSig float Standard deviation of the net signal of all inlier negative controls

gNegCtrlAveBGSubSig rNegCtrlAveBGSubSig float Average background-subtracted signal of all inlier negative controls

gNegCtrlSDevBGSubSig rNegCtrlSDevBGSubSig float Standard deviation of the background-subtracted signals of all inlier negative controls

gAveNumPixOLLo rAveNumPixOLLo integer The average number of pixels that are rejected from each feature at the low end of the intensity spectrum

gAveNumPixOLHi rAveNumPixOLHi integer The average number of pixels that are rejected from each feature at the high end of the intensity spectrum

gPixCVofHighSignalFeat rPixCVofHighSignalFeat float Average of pixel CV for features with high signal

gNumHighSignalFeat rNumHighSignalFeat integer The number of features with high signal

NonCtrlAbsAveLogRatio float This result is from a two-step calculation. Step 1 for each probe calculates the absolute average log ratio of all inlier non-control features with minimum number of replicates. Step 2 calculates the average of all absolute average log ratios calculated in step 1.

NonCtrlSDevLogRatio float The average standard deviation of log ratios of all inlier non-control probe sets with a minimum number of replicates

NonCtrlSNRLogRatio float The average of signal to noise values of the log ratio for all inlier non-control probe sets with a minimum number of replicates

Table 21 Stats results contained in the text output file (STATS table)* (continued)

Stats (Green Channel) Stats (Red Channel) Type Description

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3 Text File Parameters and Results STATS Table (ALL text output types)

eQCAbsAveLogRatio float This result is from a two-step calculation. Step 1 for each probe calculates the absolute average log ratio of all inlier spikein features with minimum number of replicates. Step 2 calculates the average of all absolute average log ratios calculated in step 1.

eQCSDevLogRatio float Average standard deviation of log ratios of all inlier spike-in probe sets with a minimum number of replicates

eQCSNRLogRatio float Average signal to noise value of log ratios of all inlier spike-in probe sets with a minimum number of replicates

AddErrorEstimateGreen float The additive error estimated for the microarray in the green channel.

AddErrorEstimateRed float The additive error estimated for the microarray in the red channel.

TotalNumFeatures integer Total number of features that show up in output file.

NonCtrlNumUpReg integer Number of up-regulated non-control probes

NonCtrlNumDownReg integer Number of down-regulated non-control probes

eQCObsVsExpLRSlope float For 2-color QC report: Slope of the linear regression fit of the plot of the expected versus observed average log ratio for each spike-in probe

eQCObsVsExpLRIntercept float For 2-color QC report: Intercept of the linear regression fit of the plot of the expected versus observed average log ratio for each spike-in probe

Table 21 Stats results contained in the text output file (STATS table)* (continued)

Stats (Green Channel) Stats (Red Channel) Type Description

Text File Parameters and Results 3 STATS Table (ALL text output types)

Feature Extraction Reference Guide 167

eQCObsVsExpCorr float For 2-color QC report: The R2 value of the linear regression fit of the plot of the expected versus observed average log ratio for each spike-in probe

NumIsNorm integer Number of features used for normalization

ROI Width

ROI Height

float The width or height (in pixels) of the region of interest (ROI) about a nominal spot location. The spotfinder determines the found centroid and spot size of the spot within the ROI.

CentroidDiffX float The average absolute of difference between nominal centroids and corresponding found centroids in X direction

CentroidDiffY float The average absolute of difference between nominal centroids and corresponding found centroids in Y direction

NumFoundFeat integer The number of features that are flagged as found

MaxNonUnifEdges float Maximum fraction of features that are non-uniform along any edge of the microarray

MaxSpotNotFoundEdges float Maximum fraction of features that are not found along any edge of the microarray

gMultDetrendRMS Fit rMultDetrendRMS Fit float Root mean square (RMS) of the fitted data points obtained from the second degree polynomial equation in Multiplicative Detrending. This gives an idea of the curvature of the surface fit to the hybridization dome in the Agilent Hybridization chambers.

Table 21 Stats results contained in the text output file (STATS table)* (continued)

Stats (Green Channel) Stats (Red Channel) Type Description

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3 Text File Parameters and Results STATS Table (ALL text output types)

gMultDetrendSurfaceAverage rMultDetrendSurfaceAverage float The average of the surface calculated by multiplicative detrending. This average is used to normalize the surface. It is a straight average over all the points in the surface.

DerivativeOfLogRatioSD float Measures the standard deviation of the probe-to-probe difference of the log ratios. This is a metric used in CGH experiments where differences in the log ratios are small on average. A smaller standard deviation here indicates less noise in the biological signals.

eQCLowSigName1 text The probe name of the eQC probe spiked in at the lowest concentration.

eQCLowSigName2 text The probe name of the eQC probe spiked in at the second lowest concentration.

eQCOneColorLogLowSignal float Agilent Spike-In Concentration-Response Statistic in the 1-color QC Report: Log of low signal for the data

eQCOneColorLogLowSignal- Error

float Agilent Spike-In Concentration-Response Statistic in the 1-color QC Report: Error in the log of low signal for the data

eQCOneColorLogHighSignal float Agilent Spike-In Concentration-Response Statistic in the 1-color QC Report: Log of high signal for the data

eQCOneColorLinFitLogLowConc float Agilent Spike-In Concentration-Response Statistic in the 1-color QC Report: Log of low concentration in the linear range of curve fit

eQCOneColorLinFitLogLow- Signal

float Agilent Spike-In Concentration-Response Statistic in the 1-color QC Report: Log of low signal in the linear range of curve fit

Table 21 Stats results contained in the text output file (STATS table)* (continued)

Stats (Green Channel) Stats (Red Channel) Type Description

Text File Parameters and Results 3 STATS Table (ALL text output types)

Feature Extraction Reference Guide 169

eQCOneColorLinFitLogHigh- Conc

float Agilent Spike-In Concentration-Response Statistic in the 1-color QC Report: Log of high concentration in the linear range of curve fit

eQCOneColorLinFitLogHigh- Signal

float Agilent Spike-In Concentration-Response Statistic in the 1-color QC Report: Log of high signal in the linear range of curve fit

eQCOneColorLinFitSlope float Agilent Spike-In Concentration-Response Statistic in the 1-color QC Report: Slope of the linear range of curve fit

eQCOneColorLinFitIntercept float Agilent Spike-In Concentration-Response Statistic in the 1-color QC Report: Intercept of the linear range of curve fit

eQCOneColorLinFitRSQ float Agilent Spike-In Concentration-Response Statistic in the 1-color QC Report: Square of the correlation coefficient of the linear range of curve fit.

eQCOneColorSpikeDetection- Limit

float The detection limit as determined by measuring the average plus 1 standard deviation of all spike-in probes below the linear concentration range. This value is the maximum of these.

gNonCtrl50PrcntBGSubSig gNonCtrl50PrcntBGSubSig float Background-subtracted signal intensity at 50th percentile for all non-control probes.

gCtrleQC50PrcntBGSubSig rCtrleQC50PrcntBGSubSig float The median background-subtracted signal for all the embedded QC probes on the microarray.

Table 21 Stats results contained in the text output file (STATS table)* (continued)

Stats (Green Channel) Stats (Red Channel) Type Description

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3 Text File Parameters and Results STATS Table (ALL text output types)

gMedPrcntCVProcSignal rMedPrcntCVProcSignal float The median %CV for replicate non-control probes using the processed signal. This value is calculated by calculating the average, SD and %CV of the processed signal of each replicated probe.

For non-control replicated probes, there must be at least 10 CVs from which to calculate a median; otherwise, -1 is reported.

The MedPrcntCVProcSignal and the MedPrcntCVBGSubSignal show if Multiplicative Detrending is having a positive effect on the data. If multiplicative detrending is helping, the MedPrcntCVProcSignal should be smaller than the MedPrcntCVBGSubSignal.

geQCMedPrcntCVProcSignal reQCMedPrcntCVProcSignal float This is the same as MedPrcntCVProcSignal, except that it is performed using the eQC SpikeIn Replicates rather than the nonControl Replicates. There must be at least 3 CVs from which to calculate a median.

gOutlierFlagger_Auto_FeatB Term

rOutlierFlagger_Auto_FeatB Term

float Applies to feature: specifies the variance due to the Poisson distributed noise; automatically calculated when OLAutoCompute is turned on

gOutlierFlagger_Auto_FeatC Term

rOutlierFlagger_Auto_FeatC Term

float Applies to feature: specifies variance due to background noise of the scanner, slide glass, and other signal-independent sources; automatically calculated when OLAutoCompute is turned on

gOutlierFlagger_Auto_BgndB Term

rOutlierFlagger_Auto_BgndB Term

float Applies to background: specifies the variance due to the Poisson distributed noise; automatically calculated when OLAutoCompute is turned on

Table 21 Stats results contained in the text output file (STATS table)* (continued)

Stats (Green Channel) Stats (Red Channel) Type Description

Text File Parameters and Results 3 STATS Table (ALL text output types)

Feature Extraction Reference Guide 171

gOutlierFlagger_Auto_BgndC Term

rOutlierFlagger_Auto_BgndC Term

float Applies to background: specifies variance due to background noise of the scanner, slide glass, and other signal-independent sources; automatically calculated when OLAutoCompute is turned on

OutlierFlagger_FeatChiSq float Confidence Interval for the feature

OutlierFlagger_BgndChiSq float Confidence Interval for the background

gXDRLowPMTSlope rXDRLowPMTSlope The slope that is multiplied by the original low intensity Mean Signal to get the XDR mean signal. Used in the linear equation relating the Mean (or Median) Signal in the low intensity scan to the scaled intensity used in the combined XDR output.

gXDRLowPMTIntercept rXDRLowPMTIntercept The intercept that is added to the Slope*LowIntensityMeanSignal to get the XDR Mean Signal. Used in the linear equation relating the Mean (or Median) Signal in the low intensity scan to the scaled intensity used in the combined XDR output.

GriddingStatus integer Indicates that the automatic image processing was flagged as

needing evaluation.

NumGeneNonUnifOL integer Number of genes that do not have any replicate features on the array where both color channels are not Feature Non-Uniform outliers. If multiple probes address the same gene, this value actually states the number of probes that have no non-uniform replicates.

TotalNumberOfReplicated Genes

integer Number of genes that have replicate features on the array.

Table 21 Stats results contained in the text output file (STATS table)* (continued)

Stats (Green Channel) Stats (Red Channel) Type Description

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3 Text File Parameters and Results STATS Table (ALL text output types)

gMultDetrendMeanSignal Difference

float This is output for miRNA only. If multiplicative detrending is turned on, the meanSignal over all replicated noncontrols is calculated before detrending and after detrending. The difference in mean signals is reported here. Because the mean signal should not change, this number should be close to 0. Without Multiplicative detrending this number is always 0.

EffectiveFeatureSizeFraction float Estimates the ratio of the effective feature size to the nominal feature size. It is calculated by looking at the ratio of the whole spot measurement versus the cookie measurement.

Feature UniformityAnomaly Fraction

float Fraction (Num/TotalNum) of the number of features looked at that had anomalous ratios. This gives a measure of the percentage of representative spots that are strange (e.g., donuts, super hot spots, hot crescents).

UsedDefaultEffectiveFeature Size

integer Reports whether or not the default effective feature size was used. If the default was used, the stat is 1. If the effective feature size was estimated, the stat value is 0.

gPercentileIntensityProcessed Signal

rPercentileIntensityProcessed Signal

float The protocol lets you enter the Percentile Value at which the intensity of the noncontrol signals is recorded. All protocols specify the 75th percentile. This number is the intensity of all the noncontrol signals in the 75th percentile. This stat is used to normalize 1-color data.

gTotalSignal99pctile float These are metrics for miRNA only. This is the value of the TotalGeneSignal for all genes at the 99th percentile.

Table 21 Stats results contained in the text output file (STATS table)* (continued)

Stats (Green Channel) Stats (Red Channel) Type Description

Text File Parameters and Results 3 STATS Table (ALL text output types)

Feature Extraction Reference Guide 173

gTotalSignal75pctile float These are metrics for miRNA only. This is the value of the TotalGeneSignal for all genes at the 75th percentile.

gNegCtrlSpread rNegCtrlSpread float The root mean square (RMS) of the preliminary spatial fit of the negative controls. It is equivalent to a standard deviation of NC signals after removal of spatial homogeneities. Used as a preliminary estimation of the noise on the array for selecting near-zero probes in spatial detrending, and conversely for excluding near-zero probes in multiplicative detrending.

gNonCtrlNumWellAboveBG rNonCtrlNumWellAboveBG integer Measure of the number of noncontrol features whose signals are well above background. Used as a metric for the number of features with significant signal.

ImageDepth string 16 bit or 20 bit

AFHold float The percentage of time, during a scan that the Autofocus assembly holds its position rather than actively maintaining focus. Typically, the value is less than 2%; however, the value will be larger if there are obstructions on the microarray that interfere with the laser beams.

gPMTVolts rPMTVolts float The voltages that Photomultipliers are set to. The voltage adjusts the spectral response of the scanner to incoming light from the lasers. In general, the higher the PMTVoltage, the higher the signals will be for fluorescent artifacts that are scanned. Typical numbers here are between 350 525 mV, but can vary depending on the PMT.

Table 21 Stats results contained in the text output file (STATS table)* (continued)

Stats (Green Channel) Stats (Red Channel) Type Description

174 Feature Extraction Reference Guide

3 Text File Parameters and Results STATS Table (ALL text output types)

GlassThickness float Expressed in microns. This represents the thickness of the microarray slide, as measured during autofocus homing. Using standard Agilent slides, the values range from 900 1000. Nominal values for non-Agilent slides are specified between 900 and 1100 for C scanners, and 900 and 1200 for B scanners.

RestrictionControl float Restriction control probes are a set of probes spanning cut sites that are not variant in samples. If the protocol is followed correctly, these probes should always give 0 signal. The final restriction control value is the minimum of the restriction control values of red channel and green channel. If restriction control probes are not present in the design, the RestrictionControl value is set to -1.

gDDN rDDN integer Direction Dependent Noise during scanning. For single-pass scanning mode (available in some Agilent scanner software), the average of background signal on an even-scan line is different from an odd-scan line. During postprocessing, the scanner control software finds the DDN difference between both directions (an average difference over the entire scan). It then calculates the even-line average minus odd-line-average. A positive DDN value means the even-line average value is greater than the odd-line average value, and a negative DDN means the even-line average is less than the odd-line average. The DDN values are written to the image file header. These stat values are not given for images that do not have DDN information.

Table 21 Stats results contained in the text output file (STATS table)* (continued)

Stats (Green Channel) Stats (Red Channel) Type Description

Text File Parameters and Results 3 STATS Table (ALL text output types)

Feature Extraction Reference Guide 175

GridHasBeenOptimized boolean

0 = False

1 = True

Indicates if grid has been adjusted for better fit as result of performing the interactively adjust corners method.

ExtractionStatus integer

0=in range;

1=out of range

This is put out only if a metric set has been run. It gives a status of the overall array.

QCMetricResults String If the Extraction Status = 0, the output says ExtractionInRange. If the Extraction Status = 1, the output says ExtractionEvaluate.

UpRandomnessRatio float Variance measure of whether or not positive Log Ratios appear to be correlated with position on the array

DownRandomnessRatio float Variance measure of whether or not negative Log Ratios appear to be correlated with position on the array

UpRandomnessSDRatio float StDev measure of whether or not positive Log Ratios appear to be correlated with position on the array

DownRandomnessSDRatio float StDev measure of whether or not negative Log Ratios appear to be correlated with position on the array

gdmr285GeneSignal rdmr285GeneSignal float These are metrics for miRNA only. This is the log10 - transformed value of TotalGeneSignal for the miRNA spikein gene dmr285 within the subtype mask 8196. If the parameter Do you want minimum signal value as 0.1? value in protocol is true then the values of TotalGeneSignal less than 0.1 will be set to 0.1 for the calculation. Otherwise the original value for TotalGeneSignal is used in the calculation.

Table 21 Stats results contained in the text output file (STATS table)* (continued)

Stats (Green Channel) Stats (Red Channel) Type Description

176 Feature Extraction Reference Guide

3 Text File Parameters and Results STATS Table (ALL text output types)

gdmr31aGeneSignal rdmr31aGeneSignal float These are metrics for miRNA only. This is the log10 - transformed value of TotalGeneSignal for the miRNA spikein gene dmr31a within the subtype mask 8196. If the parameter Do you want minimum signal value as 0.1? value in protocol is true then the values of TotalGeneSignal less than 0.1 will be set to 0.1 for the calculation. Otherwise the original value for TotalGeneSignal is used in the calculation.

gdmr6GeneSignal rdmr6GeneSignal float These are metrics for miRNA only. This is the log10 - transformed value of TotalGeneSignal for the miRNA spikein gene dmr6 within the subtype mask 8196. If the parameter Do you want minimum signal value as 0.1? value in protocol is true then the values of TotalGeneSignal less than 0.1 will be set to 0.1 for the calculation. Otherwise the original value for TotalGeneSignal is used in the calculation.

gdmr3GeneSignal rdmr3GeneSignal float These are metrics for miRNA only. This is the log10 - transformed value of TotalGeneSignal for the miRNA spikein gene dmr3 within the subtype mask 8196. If the parameter Do you want minimum signal value as 0.1? value in protocol is true then the values of TotalGeneSignal less than 0.1 will be set to 0.1 for the calculation. Otherwise the original value for TotalGeneSignal is used in the calculation.

Table 21 Stats results contained in the text output file (STATS table)* (continued)

Stats (Green Channel) Stats (Red Channel) Type Description

Text File Parameters and Results 3 STATS Table (ALL text output types)

Feature Extraction Reference Guide 177

gdmr6ProbeRatio rdmr6ProbeRatio float These are metrics for miRNA only. This is the log2 - transformed value of the ratio of the TotalGeneSignal value for the longer probe in dmr6 divided by the TotalGeneSignal value for shorter probe in dmr6. for the miRNA spikein gene dmr3 within the subtype mask 8196. The probe length can be determined from the probe name itself: for example, dmr_6_17 means 17 is the probe length. If the parameter Do you want minimum signal value as 0.1? value in protocol is true then the values of TotalGeneSignal less than 0.1 will be set to 0.1 for the calculation. Otherwise the original value for TotalGeneSignal is used in the calculation.

gdmr3ProbeRatio rdmr3ProbeRatio float These are metrics for miRNA only. This is the log2 - transformed value of the ratio of the TotalGeneSignal value for the longer probe in dmr3 divided by the TotalGeneSignal value for the shorter probe in dmr3. for the miRNA spike-in gene dmr3 within the subtype mask 8196. The probe length can be determined from the probe name itself: for example, dmr_3_17 means 17 is the probe length.If the parameter Do you want minimum signal value as 0.1? value in protocol is true then the values of TotalGeneSignal less than 0.1 will be set to 0.1 for the calculation. Otherwise the original value for TotalGeneSignal is used in the calculation.

LogRatioImbalance float This metric is for CGH only. It calculates the amount of amplifications versus deletions per chromosome to determine if there is an imbalance that falls outside of normal expectations.

Table 21 Stats results contained in the text output file (STATS table)* (continued)

Stats (Green Channel) Stats (Red Channel) Type Description

178 Feature Extraction Reference Guide

3 Text File Parameters and Results STATS Table (ALL text output types)

Metric_MetricName (Optional. Only displayed when a metric set is used.) The name of a metric in the metric set. The given value is the one that has been calculated for this metric. You can have more than one metric in a given metric set.

Metric_MetricName_IsInRange integer

1=in range;

0=out of range

(Optional. Only displayed when a metric set is used.) Indicates whether the metric was within any user-defined thresholds found in the metric set for that metric.

* Results are reported to 9 decimal places in exponential notation for all result files.

Table 21 Stats results contained in the text output file (STATS table)* (continued)

Stats (Green Channel) Stats (Red Channel) Type Description

Text File Parameters and Results 3 Feature results (FEATURES)

Feature Extraction Reference Guide 179

Feature results (FEATURES)

The bottom section of the text file gives descriptions of the results for each feature. Results are reported to 9 decimal places in exponential notation for all result files.

FULL Features Table

Table 22 Feature results contained in the FULL output text file (FULL FEATURES table)*

Features (Green) Features (Red) Types Options Description

FeatureNum integer Feature number

Row integer Feature location: row

Col integer Feature location: column

Accessions text Gene accession numbers

Chr_coord text Chromosome coordinates of the feature

SubTypeMask integer Numeric code defining the subtype of any control feature

SubTypeName integer Name of the subtype of any control feature

Start integer Indicates the place in the transcript where the probe sequence starts.

Sequence text The sequence of bases printed on the array.

ProbeUID integer Unique integer for each unique probe in a design

180 Feature Extraction Reference Guide

3 Text File Parameters and Results FULL Features Table

ControlType integer

0

1

-1

-15000

-20000

-30000

Feature control type (See XML Control Type output on page 222 for definitions.)

Control type none

Positive control

Negative control

SNP

Not probe (See Ch. 4 for definition)

Ignore (See Ch. 4 for definition)

ProbeName text An Agilent-assigned identifier for the probe synthesized on the microarray

GeneName text This is an identifier for the gene for which the probe provides expression information. The target sequence identified by the systematic name is normally a representative or consensus sequence for the gene.

SystematicName text This is an identifier for the target sequence that the probe was designed to hybridize with. Where possible, a public database identifier is used (e.g., TAIR locus identifier for Arabidopsis). Systematic name is reported ONLY if Gene name and Systematic name are different.

Description text Description of gene

PositionX

PositionY

float Found coordinates of the feature centroid in microns

Table 22 Feature results contained in the FULL output text file (FULL FEATURES table)* (continued)

Features (Green) Features (Red) Types Options Description

Text File Parameters and Results 3 FULL Features Table

Feature Extraction Reference Guide 181

LogRatio (base 10) float

-4

4

0

per feature, log of (rProcessedSignal/gProcessedSignal)

If SURROGATES are turned off, then:

if DyeNormRedSig <= 0.0 & DyeNormGreenSig > 0.0

if DyeNormRedSig > 0.0 & DyeNormGreenSig <= 0.0

if DyeNormRedSig <= 0.0 & DyeNormGreenSig <= 0.0

LogRatioError float

1000

If SURROGATES are turned off, then:

if DyeNormRedSig <= 0.0 OR DyeNormGreenSig <= 0.0

IF SURROGATES are turned on, then:

LogRatioError = error of the log ratio calculated according to the error model chosen

PValueLogRatio float Significance level of the LogRatio computed for a feature

gSurrogateUsed rSurrogateUsed float Non-zero value

0

The g(r) surrogate value used

No surrogate value used

Table 22 Feature results contained in the FULL output text file (FULL FEATURES table)* (continued)

Features (Green) Features (Red) Types Options Description

182 Feature Extraction Reference Guide

3 Text File Parameters and Results FULL Features Table

gIsFound rIsFound boolean 1 = IsFound

0 = IsNotFound

A boolean used to flag found features. The flag is applied independently in each channel.

A feature is considered Found if two conditions are true: 1) the difference between the feature signal and the local background signal is more than 1.5 times the local background noise and 2) the spot diameter is at least 0.30 times the nominal spot diameter.

gProcessedSignal rProcessedSignal float The signal left after all the Feature Extraction processing steps have been completed. In the case of one color, ProcesssedSignal contains the Multiplicatively Detrended BackgroundSubtracted Signal if the detrending is selected and helps. If the detrending does not help, this column will contain the BackgroundSubtractedSignal.

gProcessedSigError rProcessedSigError float The universal or propagated error left after all the processing steps of Feature Extraction have been completed. In the case of one color, ProcessedSignalError has had the Error Model applied and will contain at least the larger of the universal (UEM) error or the propagated error.

If multiplicative detrending is performed, ProcessedSignalError contains the error propagated from detrending. This is done by dividing the error by the normalized MultDetrendSignal.

Table 22 Feature results contained in the FULL output text file (FULL FEATURES table)* (continued)

Features (Green) Features (Red) Types Options Description

Text File Parameters and Results 3 FULL Features Table

Feature Extraction Reference Guide 183

gNumPixOLHi rNumPixOLHi integer Number of outlier pixels per feature with intensity > upper threshold set via the pixel outlier rejection method. The number is computed independently in each channel. These pixels are omitted from all subsequent calculations.

gNumPixOLLo rNumPixOLLo integer Number of outlier pixels per feature with intensity < lower threshold set via the pixel outlier rejection method. The number is computed independently in each channel. These pixels are omitted from all subsequent calculations.

NOTE: The pixel outlier method is the ONLY step that removes data in Feature Extraction.

gNumPix rNumPix integer Total number of pixels used to compute feature statistics; i.e. total number of inlier pixels/per spot; same in both channels

gMeanSignal rMeanSignal float Raw mean signal of feature from inlier pixels in green and/or red channel

gMedianSignal rMedianSignal float Raw median signal of feature from inlier pixels in green and/or red channel

gPixSDev rPixSDev float Standard deviation of all inlier pixels per feature; this is computed independently in each channel.

gPixNormIQR rPixNormIQR float The normalized Inter-quartile range of all of the inlier pixels per feature. The range is computed independently in each channel.

gBGNumPix rBGNumPix integer Total number of pixels used to compute local BG statistics per spot; i.e. total number of BG inlier pixels; same in both channels

Table 22 Feature results contained in the FULL output text file (FULL FEATURES table)* (continued)

Features (Green) Features (Red) Types Options Description

184 Feature Extraction Reference Guide

3 Text File Parameters and Results FULL Features Table

gBGMeanSignal rBGMeanSignal float Mean local background signal (local to corresponding feature) computed per channel (inlier pixels)

gBGMedianSignal rBGMedianSignal float Median local background signal (local to corresponding feature) computed per channel (inlier pixels)

gBGPixSDev rBGPixSDev float Standard deviation of all inlier pixels per local BG of each feature, computed independently in each channel

gBGPixNormIQR rBGPixNormIQR float The normalized Inter-quartile range of all of the inlier pixels per local BG of each feature. The range is computed independently in each channel.

gNumSatPix rNumSatPix integer Total number of saturated pixels per feature, computed per channel

gIsSaturated rIsSaturated boolean 1 = Saturated or 0 = Not saturated

Boolean flag indicating if a feature is saturated or not. A feature is saturated IF 50% of the pixels in a feature are above the saturation threshold.

gIsLowPMTScaled Up

rIsLowPMTScaled Up

boolean 1 = Low

0 = High

Reports if the feature signal value is from the scaled-up low signal image or from the high signal image

PixCorrelation float Ratio of estimated feature covariance in RedGreen space to product of feature standard deviation in Red Green space

The covariance of two features measures their tendency to vary together, i.e., to co-vary. In this case, it is a cumulative quantitation of the tendency of pixels belonging to a particular feature in Red and Green spaces to co-vary.

BGPixCorrelation float The same concept as above but in case of background.

Table 22 Feature results contained in the FULL output text file (FULL FEATURES table)* (continued)

Features (Green) Features (Red) Types Options Description

Text File Parameters and Results 3 FULL Features Table

Feature Extraction Reference Guide 185

gIsFeatNonUnifOL rIsFeatNonUnifOL boolean g(r)IsFeatNonUnifO L = 1 indicates Feature is a non-uniformity outlier in g(r)

Boolean flag indicating if a feature is a NonUniformity Outlier or not. A feature is non-uniform if the pixel noise of feature exceeds a threshold established for a uniform feature.

gIsBGNonUnifOL rIsBGNonUnifOL boolean g(r)IsBGNonUnifOL = 1 indicates Local background is a non-uniformity outlier in g(r)

The same concept as above but for background.

gIsFeatPopnOL rIsFeatPopnOL boolean g(r)IsFeatPopnOL = 1 indicates Feature is a population outlier in g(r)

Boolean flag indicating if a feature is a Population Outlier or not. Probes with replicate features on a microarray are examined using population statistics.

A feature is a population outlier if its signal is less than a lower threshold or exceeds an upper threshold determined using a multiplier (1.42) times the interquartile range (i.e., IQR) of the population.

gIsBGPopnOL rIsBGPopnOL boolean g(r)IsBGPopnOL = 1 indicates local background is a population outlier in g(r)

The same concept as above but for background

IsManualFlag boolean Boolean to flag features for downstream filtering in third party gene expression software.

gBGSubSignal rBGSubSignal float g(r)BGSubSignal = g(r)MeanSignal - g(r)BGUsed

Background-subtracted signal. To display the values used to calculate this variable using different background signals and settings of spatial detrend and global background adjust, see Table 34 on page 256.

Table 22 Feature results contained in the FULL output text file (FULL FEATURES table)* (continued)

Features (Green) Features (Red) Types Options Description

186 Feature Extraction Reference Guide

3 Text File Parameters and Results FULL Features Table

gBGSubSigError rBGSubSigError float Propagated standard error as computed on net g(r) background-subtracted signal.

For one color, the error model is applied to the background-subtracted signal. This will contain the larger of he universal (UEM) error or the propagated error.

BGSubSigCorrela- tion

float Ratio of estimated background- subtracted feature signal covariance in RG space to product of background- subtracted feature standard deviation in RG space

gIsPosAndSignif rIsPosAndSignif Boolean g(r)isPosAndSignif = 1 indicates Feature is positive and significant above background

Boolean flag, established via a 2-sided t-test, indicates if the mean signal of a feature is greater than the corresponding background (selected by user) and if this difference is significant. To display variables used in the t-test, see Table 34 on page 256.

gPValFeatEqBG rPValFeatEqBG float pValue from t-test of significance between g(r)Mean signal and g(r) background (selected by user)

gNumBGUsed rNumBGUsed integer Number of local background regions or features used to calculate the background used for background subtraction on this feature.

gIsWellAboveBG rIsWellAboveBG Boolean Boolean flag indicating if a feature is WellAbove Background or not,

feature passes g(r)IsPosAndSignif and additionally the g(r)BGSubSignal is greater than 2.6*g(r)BG_SD. You can change the multiplier 2.6.

Table 22 Feature results contained in the FULL output text file (FULL FEATURES table)* (continued)

Features (Green) Features (Red) Types Options Description

Text File Parameters and Results 3 FULL Features Table

Feature Extraction Reference Guide 187

gBGUsed rBGUsed float g(r)BGSubSignal = g(r)MeanSignal - g(r)BGUsed

Background used to subtract from the MeanSignal; variable also used in t-test. To display the values used to calculate this variable using different background signals and settings of spatial detrend and global background adjust, see Table 34 on page 256.

gBGSDUsed rBGSDUsed float Standard deviation of background used in g(r) channel; variable also used in t-test and surrogate algorithms. To display the values used to calculate this variable using different background signals and settings of spatial detrend and global background adjust, see Table 34 on page 256.

IsNormalization boolean 1 = Feature used; 0 = Feature not used

A boolean flag which indicates if a feature is used to measure dye bias

gDyeNormSignal rDyeNormSignal float The dye-normalized signal in the indicated channel

gDyeNormError rDyeNormError float The standard error associated with the dye-normalized signal

DyeNormCorrelation float Dye-normalized red and green pixel correlation

ErrorModel 0 = Propagated model chosen by you or by software

1 = Universal error model chosen by you or by software

Indicates the error model that you chose for Feature Extraction or that the software uses if you have chosen the Most Conservative option

xDev float A signal-to-noise parameter used to calculate pValue; calculated differently depending on error model chosen

Table 22 Feature results contained in the FULL output text file (FULL FEATURES table)* (continued)

Features (Green) Features (Red) Types Options Description

188 Feature Extraction Reference Guide

3 Text File Parameters and Results FULL Features Table

gSpatialDetrendIsIn FilteredSet

rSpatialDetrendIsIn FilteredSet

boolean 1 = Feature in filtered set

0 = Feature not in filtered set

Set to true for a given feature if it is part of the filtered set used to detrend the background. This feature is considered part of the locally weighted lowest x% of features as defined by the DetrendLowPassPercentage.

gSpatialDetrend SurfaceValue

rSpatialDetrend SurfaceValue

float Value of the smoothed surface calculated by the Spatial detrend algorithm

gIsLowEnoughAdd Detrend

rIsLowEnoughAdd Detrend

boolean These points are considered to be in the background for the purposes of spatial detrending and multiplicative detrending. If the Boolean value is true for a given point, it will be used in spatial detrending and not in multiplicative detrending (depends on parameters).

SpotExtentX float Diameter of the spot (X-axis)

SpotExtentY float Diameter of the spot (Y-axis)

gNetSignal rNetSignal float MeanSignal minus DarkOffset

gTotalProbeSignal float This signal is the robust average of all the processed green signals for each replicated probe multiplied by the total number of probe replicates, the EffectiveFeature SizeFraction, the Nominal Spot Area and the Weight. For miRNA analyses

gTotalProbeError float This error is the robust average of all the processed green signal errors for each replicated probe multiplied by the total number of probe replicates, the EffectiveFeature SizeFraction, the Nominal Spot Area and the Weight. For miRNA analyses

Table 22 Feature results contained in the FULL output text file (FULL FEATURES table)* (continued)

Features (Green) Features (Red) Types Options Description

Text File Parameters and Results 3 FULL Features Table

Feature Extraction Reference Guide 189

gTotalGeneSignal float This signal is the sum of the total probe signals in the green channel per gene. For miRNA analyses.

gTotalGeneError float This error is the square root of the sum of the squares of the TotalProbeError. For miRNA analyses.

gIsGeneDetected boolean Lets you know if the gene was detected on the miRNA microarray.

gMultDetrendSignal rMultDetrendSignal float A surface is fitted through the log of the background-subtracted signal to look for multiplicative gradients. A normalized version of that surface interpolated at each point of the microarray is stored in MultDetrendSignal. The surface is normalized by dividing each point by the overall average of the surface. That average is stored in MultDetrendSurfaceAverage as a statistic. 1-color only

gProcessed Background

rProcessed Background

float Indicates the Background signal that was selected to be used (Mean or Median).

gProcessedBkng Error

rProcessedBkng Error

float Indicates the Background error that was selected to be used (PixSD or NormIQR)

IsUsedBGAdjust boolean 1 = Feature used 0 = Feature not used

A Boolean used to flag features used for computation of global BG offset

gInterpolatedNeg CtrlSub

rInterpolatedNeg CtrlSub

float Value at the polynomial fit of the negative controls.

gIsInNegCtrlRange rIsInNegCtrlRange boolean Set to true for a given feature if its signal intensity is in the negative control range.

gIsUsedInMD rIsUsedInMD boolean Indicates whether this feature was included in the set used to generate the multiplicative detrend surface.

* Results are reported to 9 decimal places in exponential notation for all result files.

Table 22 Feature results contained in the FULL output text file (FULL FEATURES table)* (continued)

Features (Green) Features (Red) Types Options Description

190 Feature Extraction Reference Guide

3 Text File Parameters and Results COMPACT Features Table

COMPACT Features Table

Table 23 Feature results contained in the COMPACT output text file (COMPACT FEATURES table)*

Features (Green) Features (Red) Types Options Description

FeatureNum integer Feature number

Row integer Feature location: row

Col integer Feature location: column

SubTypeMask integer Numeric code defining the subtype of any control feature

ControlType integer

0

1

-1

-15000

-20000

-30000

Feature control type (See XML Control Type output on page 222 for definitions.)

Control type none

Positive control

Negative control

SNP

Not probe (See Ch. 4 for definition)

Ignore (See Ch. 4 for definition)

ProbeName text An Agilent-assigned identifier for the probe synthesized on the microarray

SystematicName text This is an identifier for the target sequence that the probe was designed to hybridize with. Where possible, a public database identifier is used (e.g., TAIR locus identifier for Arabidopsis). Systematic name is reported ONLY if Gene name and Systematic name are different.

Position X Position Y

float Found coordinates of the feature centroid in microns

Text File Parameters and Results 3 COMPACT Features Table

Feature Extraction Reference Guide 191

LogRatio (base 10) float

-4

4

0

per feature, log of (rProcessedSignal/gProcessedSignal)

If SURROGATES are turned off, then:

if DyeNormRedSig <= 0.0 & DyeNormGreenSig > 0.0

if DyeNormRedSig > 0.0 & DyeNormGreenSig <= 0.0

if DyeNormRedSig <= 0.0 & DyeNormGreenSig <= 0.0

LogRatioError float

1000

If SURROGATES are turned off, then:

if DyeNormRedSig <= 0.0 OR DyeNormGreenSig <= 0.0

IF SURROGATES are turned on, then:

LogRatioError = error of the log ratio calculated according to the error model chosen

PValueLogRatio float Significance level of the Log Ratio computed for a feature

gProcessedSignal rProcessedSignal float The signal left after all the Feature Extraction processing steps have been completed. In the case of one color, ProcesssedSignal contains the Multiplicatively Detrended BackgroundSubtracted Signal if the detrending is selected and helps. If the detrending does not help, this column will contain the BackgroundSubtractedSignal.

Table 23 Feature results contained in the COMPACT output text file (COMPACT FEATURES table)* (continued)

Features (Green) Features (Red) Types Options Description

192 Feature Extraction Reference Guide

3 Text File Parameters and Results COMPACT Features Table

gProcessedSigError rProcessedSigError float The universal or propagated error left after all the processing steps of Feature Extraction have been completed. In the case of one color, ProcessedSignalError has had the Error Model applied and will contain at least the larger of the universal (UEM) error or the propagated error.

If multiplicative detrending is performed, ProcessedSignalError contains the error propagated from detrending. This is done by dividing the error by the normalized MultDetrendSignal.

gMedianSignal rMedianSignal float Raw median signal of feature in green (red) channel (inlier pixels)

gBGMedianSignal rBGMedianSignal float Median local background signal (local to corresponding feature) computed per channel (inlier pixels)

gBGPixSDev rBGPixSDev float Standard deviation of all inlier pixels per local BG of each feature, computed independently in each channel

gIsSaturated rIsSaturated boolean 1 = Saturated or 0 = Not saturated

Boolean flag indicating if a feature is saturated or not. A feature is saturated IF 50% of the pixels in a feature are above the saturation threshold.

gIsLowPMTScaled Up

rIsLowPMTScaled Up

boolean 1 = Low

0 = High

Reports if the feature signal value is from the scaled-up low signal image or from the high signal image

gIsFeatNonUnifOL rIsFeatNonUnifOL boolean g(r)IsFeatNonUnifO L = 1 indicates Feature is a non-uniformity outlier in g(r)

Boolean flag indicating if a feature is a NonUniformity Outlier or not. A feature is non-uniform if the pixel noise of feature exceeds a threshold established for a uniform feature.

Table 23 Feature results contained in the COMPACT output text file (COMPACT FEATURES table)* (continued)

Features (Green) Features (Red) Types Options Description

Text File Parameters and Results 3 COMPACT Features Table

Feature Extraction Reference Guide 193

gIsBGNonUnifOL rIsBGNonUnifOL boolean g(r)IsBGNonUnifOL = 1 indicates Local background is a non-uniformity outlier in g(r)

The same concept as above but for background.

gIsFeatPopnOL rIsFeatPopnOL boolean g(r)IsFeatPopnOL = 1 indicates Feature is a population outlier in g(r)

Boolean flag indicating if a feature is a Population Outlier or not. Probes with replicate features on a microarray are examined using population statistics.

A feature is a population outlier if its signal is less than a lower threshold or exceeds an upper threshold determined using a multiplier (1.42) times the interquartile range (i.e., IQR) of the population.

gIsBGPopnOL rIsBGPopnOL boolean g(r)IsBGPopnOL = 1 indicates local background is a population outlier in g(r)

The same concept as above but for background

IsManualFlag boolean Flags features for downstream filtering in third party gene expression software.

gBGSubSignal rBGSubSignal float g(r)BGSubSignal = g(r)MeanSignal - g(r)BGUsed

Background-subtracted signal. To display the values used to calculate this variable using different background signals and settings of spatial detrend and global background adjust, see Table 34 on page 256.

gIsPosAndSignif rIsPosAndSignif boolean g(r)isPosAndSignif = 1 indicates Feature is positive and significant above background

Boolean flag, established via a 2-sided t-test, indicates if the mean signal of a feature is greater than the corresponding background (selected by user) and if this difference is significant. To display variables used in the t-test, see Table 34 on page 256.

Table 23 Feature results contained in the COMPACT output text file (COMPACT FEATURES table)* (continued)

Features (Green) Features (Red) Types Options Description

194 Feature Extraction Reference Guide

3 Text File Parameters and Results COMPACT Features Table

gIsWellAboveBG rIsWellAboveBG boolean Boolean flag indicating if a feature is WellAbove Background or not,

feature passes g(r)IsPosAndSignif and additionally the g(r)BGSubSignal is greater than 2.6*g(r)BG_SD. You can change the multiplier 2.6.

SpotExtentX float Diameter of the spot (X-axis)

gBGMeanSignal rBGMeanSignal float Mean local background signal (local to corresponding feature) computed per channel (inlier pixels)

gTotalProbeSignal float This signal is the robust average of all the processed green signals for each replicated probe multiplied by the total number of probe replicates, the EffectiveFeature SizeFraction, the Nominal Spot Area and the Weight. For miRNA analyses

gTotalProbeError float This error is the robust average of all the processed green signal errors for each replicated probe multiplied by the total number of probe replicates, the EffectiveFeature SizeFraction, the Nominal Spot Area and the Weight. For miRNA analyses

gTotalGeneSignal float This signal is the sum of the total probe signals in the green channel per gene. For miRNA analyses.

gTotalGeneError float This error is the square root of the sum of the squares of the TotalProbeError. For miRNA analyses.

gIsGeneDetected boolean Lets you know if the gene was detected on the miRNA microarray.

* Results are reported to 9 decimal places in exponential notation for all result files.

Table 23 Feature results contained in the COMPACT output text file (COMPACT FEATURES table)* (continued)

Features (Green) Features (Red) Types Options Description

Text File Parameters and Results 3 QC Features Table

Feature Extraction Reference Guide 195

QC Features Table

Table 24 Feature results contained in the QC output text file (QC FEATURES table)

Features (Green) Features (Red) Types Options Description

FeatureNum integer Feature number

Row integer Feature location: row

Col integer Feature location: column

SubTypeMask integer Numeric code defining the subtype of any control feature

ControlType integer

0

1

-1

-15000

-20000

-30000

Feature control type (See XML Control Type output on page 222 for definitions.)

Control type none

Positive control

Negative control

SNP

Not probe (See Ch. 4 for definition)

Ignore (See Ch. 4 for definition)

ProbeName text An Agilent-assigned identifier for the probe synthesized on the microarray

SystematicName text This is an identifier for the target sequence that the probe was designed to hybridize with. Where possible, a public database identifier is used (e.g., TAIR locus identifier for Arabidopsis). Systematic name is reported ONLY if Gene name and Systematic name are different.

Description text Description of gene

196 Feature Extraction Reference Guide

3 Text File Parameters and Results QC Features Table

PositionX

PositionY

float Found coordinates of the feature centroid in microns

LogRatio (base 10) float

-4

4

0

per feature, log of (rProcessedSignal/gProcessedSignal)

If SURROGATES are turned off, then:

if DyeNormRedSig <= 0.0 & DyeNormGreenSig > 0.0

if DyeNormRedSig > 0.0 & DyeNormGreenSig <= 0.0

if DyeNormRedSig <= 0.0 & DyeNormGreenSig <= 0.0

LogRatioError float

1000

If SURROGATES are turned off, then:

if DyeNormRedSig <= 0.0 OR DyeNormGreenSig <= 0.0

IF SURROGATES are turned on, then:

LogRatioError = error of the log ratio calculated according to the error model chosen

PValueLogRatio float Significance level of the LogRatio computed for a feature

Features (Green) Features (Red) Types Options Description

Text File Parameters and Results 3 QC Features Table

Feature Extraction Reference Guide 197

gProcessedSignal rProcessedSignal float The signal left after all the Feature Extraction processing steps have been completed. In the case of one color, ProcesssedSignal contains the Multiplicatively Detrended BackgroundSubtracted Signal if the detrending is selected and helps. If the detrending does not help, this column will contain the BackgroundSubtractedSignal.

gProcessedSigError rProcessedSigError float The universal or propagated error left after all the processing steps of Feature Extraction have been completed. In the case of one color, ProcessedSignalError has had the Error Model applied and will contain at least the larger of the universal (UEM) error or the propagated error.

If multiplicative detrending is performed, ProcessedSignalError contains the error propagated from detrending. This is done by dividing the error by the normalized MultDetrendSignal.

gNumPixOLHi rNumPixOLHi integer Number of outlier pixels per feature with intensity > upper threshold set via the pixel outlier rejection method. The number is computed independently in each channel. These pixels are omitted from all subsequent calculations.

gNumPixOLLo rNumPixOLLo integer Number of outlier pixels per feature with intensity < lower threshold set via the pixel outlier rejection method. The number is computed independently in each channel. These pixels are omitted from all subsequent calculations.

NOTE: The pixel outlier method is the ONLY step that removes data in Feature Extraction.

Features (Green) Features (Red) Types Options Description

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gNumPix rNumPix integer Total number of pixels used to compute feature statistics; i.e. total number of inlier pixels/per spot; same in both channels

gMeanSignal rMeanSignal float Raw mean signal of feature from inlier pixels in green and/or red channel

gMedianSignal rMedianSignal float Raw median signal of feature from inlier pixels in green and/or red channel

gPixSDev rPixSDev float Standard deviation of all inlier pixels per feature; this is computed independently in each channel.

gBGMeanSignal rBGMeanSignal float Mean local background signal (local to corresponding feature) computed per channel (inlier pixels)

gBGMedianSignal rBGMedianSignal float Median local background signal (local to corresponding feature) computed per channel (inlier pixels)

gBGPixSDev rBGPixSDev float Standard deviation of all inlier pixels per local BG of each feature, computed independently in each channel

gIsSaturated rIsSaturated boolean 1 = Saturated or 0 = Not saturated

Boolean flag indicating if a feature is saturated or not. A feature is saturated IF 50% of the pixels in a feature are above the saturation threshold.

gIsLowPMTScaled Up

rIsLowPMTScaled Up

boolean 1 = Low

0 = High

Reports if the feature signal value is from the scaled-up low signal image or from the high signal image

BGPixCorrelation float The same concept as above but in case of background.

gIsFeatNonUnifOL rIsFeatNonUnifOL boolean g(r)IsFeatNonUnifO L = 1 indicates Feature is a non-uniformity outlier in g(r)

Boolean flag indicating if a feature is a NonUniformity Outlier or not. A feature is non-uniform if the pixel noise of feature exceeds a threshold established for a uniform feature.

Features (Green) Features (Red) Types Options Description

Text File Parameters and Results 3 QC Features Table

Feature Extraction Reference Guide 199

gIsBGNonUnifOL rIsBGNonUnifOL boolean g(r)IsBGNonUnifOL = 1 indicates Local background is a non-uniformity outlier in g(r)

The same concept as above but for background.

gIsFeatPopnOL rIsFeatPopnOL boolean g(r)IsFeatPopnOL = 1 indicates Feature is a population outlier in g(r)

Boolean flag indicating if a feature is a Population Outlier or not. Probes with replicate features on a microarray are examined using population statistics.

A feature is a population outlier if its signal is less than a lower threshold or exceeds an upper threshold determined using a multiplier (1.42) times the interquartile range (i.e., IQR) of the population.

gIsBGPopnOL rIsBGPopnOL boolean g(r)IsBGPopnOL = 1 indicates local background is a population outlier in g(r)

The same concept as above but for background

IsManualFlag boolean Flags features for downstream filtering in third party gene expression software.

gBGSubSignal rBGSubSignal float g(r)BGSubSignal = g(r)MeanSignal - g(r)BGUsed

Background-subtracted signal. To display the values used to calculate this variable using different background signals and settings of spatial detrend and global background adjust, see Table 34 on page 256.

gIsPosAndSignif rIsPosAndSignif Boolean g(r)isPosAndSignif = 1 indicates Feature is positive and significant above background

Boolean flag, established via a 2-sided t-test, indicates if the mean signal of a feature is greater than the corresponding background (selected by user) and if this difference is significant. To display variables used in the t-test, see Table 34 on page 256.

Features (Green) Features (Red) Types Options Description

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gIsWellAboveBG rIsWellAboveBG Boolean Boolean flag indicating if a feature is WellAbove Background or not,

feature passes g(r)IsPosAndSignif and additionally the g(r)BGSubSignal is greater than 2.6*g(r)BG_SD. You can change the multiplier 2.6.

SpotExtentX float Diameter of the spot (X-axis)

gBGMeanSignal rBGMeanSignal float Mean local background signal (local to corresponding feature) computed per channel (inlier pixels)

gTotalProbeSignal float This signal is the robust average of all the processed green signals for each replicated probe multiplied by the total number of probe replicates, the EffectiveFeature SizeFraction, the Nominal Spot Area and the Weight. For miRNA analyses

gTotalProbeError float This error is the robust average of all the processed green signal errors for each replicated probe multiplied by the total number of probe replicates, the EffectiveFeature SizeFraction, the Nominal Spot Area and the Weight. For miRNA analyses

gTotalGeneSignal float This signal is the sum of the total probe signals in the green channel per gene. For miRNA analyses.

gTotalGeneError float This error is the square root of the sum of the squares of the TotalProbeError. For miRNA analyses.

gIsGeneDetected boolean Lets you know if the gene was detected on the miRNA microarray.

Features (Green) Features (Red) Types Options Description

Text File Parameters and Results 3 MINIMAL Features Table

Feature Extraction Reference Guide 201

MINIMAL Features Table

Table 25 Feature results contained in the MINIMAL output text file (MINIMAL FEATURES table)

Features (Green) Features (Red) Types Options Description

FeatureNum integer Feature number

Row integer Feature location: row

Col integer Feature location: column

ControlType integer

0

1

-1

-15000

-20000

-30000

Feature control type (See XML Control Type output on page 222 for definitions.)

Control type none

Positive control

Negative control

SNP

Not probe (See Ch. 4 for definition)

Ignore (See Ch. 4 for definition)

ProbeName text An Agilent-assigned identifier for the probe synthesized on the microarray

SystematicName text This is an identifier for the target sequence that the probe was designed to hybridize with. Where possible, a public database identifier is used (e.g., TAIR locus identifier for Arabidopsis). Systematic name is reported ONLY if Gene name and Systematic name are different.

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LogRatio (base 10) float

-4

4

0

per feature, log of (rProcessedSignal/gProcessedSignal)

If SURROGATES are turned off, then:

if DyeNormRedSig <= 0.0 & DyeNormGreenSig > 0.0

if DyeNormRedSig > 0.0 & DyeNormGreenSig <= 0.0

if DyeNormRedSig <= 0.0 & DyeNormGreenSig <= 0.0

LogRatioError float

1000

If SURROGATES are turned off, then:

if DyeNormRedSig <= 0.0 OR DyeNormGreenSig <= 0.0

IF SURROGATES are turned on, then:

LogRatioError = error of the log ratio calculated according to the error model chosen

PValueLogRatio float Significance level of the LogRatio computed for a feature

gProcessedSignal rProcessedSignal float The signal left after all the Feature Extraction processing steps have been completed. In the case of one color, ProcesssedSignal contains the Multiplicatively Detrended BackgroundSubtracted Signal if the detrending is selected and helps. If the detrending does not help, this column will contain the BackgroundSubtractedSignal.

Features (Green) Features (Red) Types Options Description

Text File Parameters and Results 3 MINIMAL Features Table

Feature Extraction Reference Guide 203

gProcessedSigError rProcessedSigError float The universal or propagated error left after all the processing steps of Feature Extraction have been completed. In the case of one color, ProcessedSignalError has had the Error Model applied and will contain at least the larger of the universal (UEM) error or the propagated error.

If multiplicative detrending is performed, ProcessedSignalError contains the error propagated from detrending. This is done by dividing the error by the normalized MultDetrendSignal.

gNumPixOLHi rNumPixOLHi integer Number of outlier pixels per feature with intensity > upper threshold set via the pixel outlier rejection method. The number is computed independently in each channel. These pixels are omitted from all subsequent calculations.

gMedianSignal rMedianSignal float Raw median signal of feature from inlier pixels in green and/or red channel

gPixNormIQR rPixNormIQR float The normalized Inter-quartile range of all of the inlier pixels per feature. The range is computed independently in each channel.

gIsSaturated rIsSaturated boolean 1 = Saturated or 0 = Not saturated

Boolean flag indicating if a feature is saturated or not. A feature is saturated IF 50% of the pixels in a feature are above the saturation threshold.

gIsFeatNonUnifOL rIsFeatNonUnifOL boolean g(r)IsFeatNonUnifO L = 1 indicates Feature is a non-uniformity outlier in g(r)

Boolean flag indicating if a feature is a NonUniformity Outlier or not. A feature is non-uniform if the pixel noise of feature exceeds a threshold established for a uniform feature.

Features (Green) Features (Red) Types Options Description

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gIsFeatPopnOL rIsFeatPopnOL boolean g(r)IsFeatPopnOL = 1 indicates Feature is a population outlier in g(r)

Boolean flag indicating if a feature is a Population Outlier or not. Probes with replicate features on a microarray are examined using population statistics.

A feature is a population outlier if its signal is less than a lower threshold or exceeds an upper threshold determined using a multiplier (1.42) times the interquartile range (i.e., IQR) of the population.

gIsWellAboveBG rIsWellAboveBG Boolean Boolean flag indicating if a feature is WellAbove Background or not,

feature passes g(r)IsPosAndSignif and additionally the g(r)BGSubSignal is greater than 2.6*g(r)BG_SD. You can change the multiplier 2.6.

Features (Green) Features (Red) Types Options Description

Text File Parameters and Results 3 Other text result file annotations

Feature Extraction Reference Guide 205

Other text result file annotations

The following public accession numbers may or may not show up in the Feature Results section of the output text file.

Table 26 Public accession numbers in the output text file

Abbreviation Description

dbj DNA Database of Japan

emb EMBL

gb GenBank

gbpri GenBank primate nucleotide accession number

gi GenBank Gene Identifier

gp GenPept protein identification number

mgi Mouse Genome Informatics

pdb Brookhaven Protein data bank

pir NBRF PIR

prf Protein Research Foundation

rafl RIKEN full Length cDNA

ref RefSeq

sp SwissProt

tair The Arabidopsis Information Resource

ug UniGenelocuslink: LocusLink ID

wi Whitehead

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207Agilent Technologies

Agilent Feature Extraction 12.2 Reference Guide

4 MAGE-ML (XML) File Results

How Agilent output file formats are used by databases 208

MAGE-ML results 209

Helpful hints for transferring Agilent output files 222

This chapter provides a listing of MAGE- ML results in the form of tables. Refer to these tables when you want to know the results reported in a particular file. This chapter also contains a section on TIFF files and formats.

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How Agilent output file formats are used by databases

Pattern files should be loaded to the database via FTP if possible to ensure that the pattern element, name attribute, is used to name the pattern.

Data analysis programs must match up information about the layout and annotation of the microarray features with the profile result files for each microarray within their databases. Agilent provides this design information for its microarrays in a variety of file formats, including GAL and MAGE- ML. These files describe the gene probes and their number and spacing on the microarray. Profile result files contain the signal and error information for each of the hybridized gene probes on the microarray.

Both pattern files and profile result files contain information that can be formatted in several ways: tab- delimited text format or an XML format, MAGE- ML.

Agilent only supports GEML2 Pattern files and MAGE- ML profiles for use with Rosetta Resolver. The pattern name in Rosetta Resolver should match the profile pattern name embedded in the profile data so that the data can be correctly associated. To do this, use the pattern autoimport function in Rosetta Resolver or correctly specify the pattern name when manually importing the pattern. (The Agilent pattern name in most cases is Agilent- xxxxxx where the xxxxxx is the AMADID number of the microarray.)

For transfer of data into GeneSpring, the pattern information can be obtained from within the Feature Extraction profile tab text file or can be obtained by download from the GeneSpring website.

MAGE-ML (XML) File Results 4 MAGE-ML results

Feature Extraction Reference Guide 209

MAGE-ML results

Differences between MAGE-ML and text result files

The MAGE- ML result file includes most of the same parameters, statistics and results as the FULL text result file with the following differences:

Scanner control parameters are included in the file.

Some Feature Extraction parameter names (FE PARAMS table) have been changed to accommodate Rosetta Resolver terminology.

MAGE result file includes all information included in the FEATURES table except for annotations, deletion control information and spot size information.

Feature results (FEATURES table) are associated with quantitation types as defined by the Object Management Group in its Gene Expression Specification paper of February 2003 V.1. These types are listed here:

Measured Signal

Derived Signal

Ratio

Confidence Indicatorserror and p- value

Specialized Quantitation Type (SQT) includes all other data

Full and Compact Output Packages

In the Properties sheet for the project you can select if you want the MAGE- ML result file to contain all the possible columns and results (Full) or a reduced set of results (Compact).

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MAGE- ML files can also be compressed before they are sent via FTP. Compressed MAGE- ML files further reduces the size of the file to decrease the transfer time. Use both Compact and Compressed MAGE- ML files for Resolver. The Compact package contains only those columns required by Resolver, GeneSpring, CGH Analytics and Chip Analytics.

In the Compact version of the MAGE- ML file, the entire FEPARAMS section is included. MAGE- ML has a rich mechanism for describing protocols and protocol parameters.

Tables for Full Output Package

Table 27 Scan protocol parameters in MAGE-ML result file

Parameter Description

Image acquisition identifier Barcode or identifier for microarray

Log information Warnings and errors during run

Activity date Time stamp for scanner run

Scanner information Information such as name, make model and serial number of scanner

Operator Person that runs scanner

ScanNumber Number of the scan associated with the values listed in this table

Red.LASER_POWER_VALUE Value of laser power in red channel

Green.LASER_POWER_VALUE Value of laser power in green channel

Red.PMT_GAIN_VALUE Photomultiplier gain in red channel

Green.PMT_GAIN_VALUE Photomultiplier gain in green channel

Red.Saturation_Value Signal value beyond which signal is saturated in the red channel

Green.Saturation_Value Signal value beyond which signal is saturated in the green channel

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Feature Extraction Reference Guide 211

T

MICRONS_PER_PIXEL_X Radius of pixel in the x direction

MICRONS_PER_PIXEL_Y Radius of pixel in the y direction

GlassThickness Thickness of microarray slide

Red.DarkOffsetAverage Dark offset data per image in red channel as measured by scanner

Green.DarkOffsetAverage Dark offset data per image in green channel as measured by scanner

PercentAutoFocusHold Amount of movement in the autofocus because of fluctuations in the glass

DarkOffsetSubtracted Resulting signal when dark offset value is subtracted

Table 28 Feature Extraction protocol parameters in MAGE-ML result file Differences between FEPARAMS in text file and MAGE-ML file

Text File FEPARAMS MAGE-ML File FEPARAMS

Ratio_ErrorModel Error Model

Ratio_AddErrorRed Red.ADDITIVE_ERROR

Ratio_AddErrorGreen Green.ADDITIVE_ERROR

Ratio_MultErrorRed Red.MULTIPLICATIVE_ERROR

Ratio_MultErrorGreen Green.MULTIPLICATIVE_ERROR

Table 27 Scan protocol parameters in MAGE-ML result file (continued)

Parameter Description

NOTE For 1-color, red signals and log ratios are not included in the MAGE-ML output files.

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Table 29 Feature results (Full) contained in the MAGE-ML (FEATURES table)

Quant Type

Features (Green) Features (Red) Options Description

SQT* X_IMAGE_POSITION

Y_IMAGE_POSITION

Found coordinates of the feature centroid

SQT SpotExtentX

SpotExtentY

Diameter of the spot (X- or Y-Axis)

Ratio LogRatio (base 10)

-4

4

0

log(REDsignal/GREENsignal) per feature (processed signals used to calculate log ratio)

If SURROGATES are turned off, then:

if DyeNormRedSig <= 0.0 & DyeNormGreenSig > 0.0

if DyeNormRedSig > 0.0 & DyeNormGreenSig <= 0.0

if DyeNormRedSig <= 0.0 & DyeNormGreenSig <= 0.0

Error LogRatioError

1000

If SURROGATES are turned off, then:

if DyeNormRedSig <= 0.0 OR DyeNormGreenSig <= 0.0

IF SURROGATES are turned on, then:

LogRatioError = error of the log ratio calculated according to the error model chosen

PValue PValueLogRatio Significance level of the Log Ratio computed for a feature

SQT gSurrogateUsed rSurrogateUsed Non-zero value

0

The g(r) surrogate value used

No surrogate value used

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Feature Extraction Reference Guide 213

SQT gIsFound rIsFound 1 = IsFound

0 = IsNotFound

A boolean used to flag found (strong) features. The flag is applied independently in each channel.

A feature is considered found if the calculated spot centroid is within the bounds of the spot deviation limit with respect to corresponding nominal centroid. NOTE: IsFound was previously termed IsStrong.

Derived Signal

Green.DerivedSignal Red.DerivedSignal The propagated feature signal, per channel, used for computation of log ratio

Error Green.ProcessedSig Error

Red.ProcessedSig Error

Standard error of propagated feature signal, per channel

SQT gNumPixOLHi rNumPixOLHi Number of outlier pixels per feature with intensity > upper threshold set via the pixel outlier rejection method. The number is computed independently in each channel. These pixels are omitted from all subsequent calculations.

SQT gNumPixOLLo rNumPixOLLo Number of outlier pixels per feature with intensity < lower threshold set via the pixel outlier rejection method. The number is computed independently in each channel.

NOTE: The pixel outlier method is the ONLY step that removes data in Feature Extraction.

SQT gNumPix rNumPix Total number of pixels used to compute feature statistics, i.e., total number of inlier pixels/per spot, same in both channels

Table 29 Feature results (Full) contained in the MAGE-ML (FEATURES table)

Quant Type

Features (Green) Features (Red) Options Description

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Measur ed Signal

Green.Measured Signal

Red.Measured Signal

Raw mean signal of feature in green (red) channel

SQT gMedianSignal rMedianSignal Raw median signal of feature in green (red) channel

SQT gNetSignal rNetSignal MeanSignal minus DarkOffset

Error Green.PixSDev Red.PixSDev Standard deviation of all inlier pixels per feature. This is computed independently in each channel.

SQT gBGNumPix rBGNumPix Total Number of pixels used to compute Local BG statistics per spot; i.e., total number of BG inlier pixels. This number is computed independently in each channel.

Measur ed Signal

Green.Background Red.Background Mean local background signal (local to corresponding feature) computed per channel

SQT gBGMedianSignal rBGMedianSignal Median local background signal (local to corresponding feature) computed per channel

Error Green.BGPixSDev Red.BGPixSDev Standard deviation of all inlier pixels per Local BG of each feature, computed independently in each channel

SQT gNumSatPix rNumSatPix Total number of saturated pixels per feature, computed per channel

SQT gIsSaturated rIsSaturated 1 = Saturated or 0 = Not saturated

Integer indicating if a feature is saturated or not. A feature is saturated IF 50% of the pixels in a feature are above the saturation threshold.

Table 29 Feature results (Full) contained in the MAGE-ML (FEATURES table)

Quant Type

Features (Green) Features (Red) Options Description

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Feature Extraction Reference Guide 215

SQT gIsLowPMTScaledUp rIsLowPMTScaledUp 1 = Low

0 = High

For XDR features, this is an integer indicating if the low PMT value was used for the calculations, or the high value.

SQT PixCorrelation Ratio of estimated feature covariance in RedGreen space to product of feature Standard Deviation in Red Green space

The covariance of two features measures their tendency to vary together, i.e., to co-vary. In this case, it is a cumulative quantitation of the tendency of pixels belonging to a particular feature in Red and Green spaces to co-vary.

float BGPixCorrelation The same concept as above but in case of background

SQT gIsFeatNonUnifOL rIsFeatNonUnifOL g(r)IsFeatNonUnifOL = 1 indicates Feature is a non-uniformity outlier in g(r)

Integer indicating if a feature is a NonUniformity Outlier or not. A feature is non-uniform if the pixel noise of feature exceeds a threshold established for a uniform feature.

SQT gIsBGNonUnifOL rIsBGNonUnifOL g(r)IsBGNonUnifOL = 1 indicates Local background is a non-uniformity outlier in g(r)

The same concept as above but for background

Table 29 Feature results (Full) contained in the MAGE-ML (FEATURES table)

Quant Type

Features (Green) Features (Red) Options Description

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SQT gIsFeatPopnOL rIsFeatPopnOL g(r)IsFeatPopnOL = 1 indicates Feature is a population outlier in g(r)

Boolean flag indicating if a feature is a Population Outlier or not. Probes with replicate features on a microarray are examined using population statistics.

A feature is a population outlier if its signal is less than a lower threshold or exceeds an upper threshold determined using a multiplier (1.42) times the interquartile range (i.e., IQR) of the population.

SQT gIsBGPopnOL rIsBGPopnOL g(r)IsBGPopnOL = 1 indicates local background is a population outlier in g(r)

The same concept as above but for background

SQT IsManualFlag

SQT gBGSubSignal rBGSubSignal gBGSubSignal = gMeanSignal - gBGUsed

Background-subtracted signal

To display the values used to calculate this variable using different background signals and settings of spatial detrend and global background adjust, see Table 34 on page 256.

Error gBGSubSigError rBGSubSigError Propagated standard error as computed on net g(r) background-subtracted signal

SQT BGSubSigCorrelation Ratio of estimated background- subtracted feature signal covariance in RG space to product of background- subtracted feature Standard Deviation in RG space

Table 29 Feature results (Full) contained in the MAGE-ML (FEATURES table)

Quant Type

Features (Green) Features (Red) Options Description

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SQT gIsPosAndSignif rIsPosAndSignif g(r)isPosAndSignif = 1 indicates Feature is positive and significant above background

Boolean flag, established via a 2-sided t-test, indicates if the mean signal of a feature is greater than the corresponding background (selected by user) and if this difference is significant. To display variables used in the t-test, see Table 34 on page 256.

SQT gPValFeatEqBG rPValFeatEqBG P-value from t-test of significance between g(r)Mean signal and g(r) background

SQT gIsWellAboveBG rIsWellAboveBG Boolean flag indicating if a feature is WellAbove Background or not

Feature passes g(r)IsPosAndSignif and additionally the g(r)BGSubSignal is greater than 2.6*g(r)BGSDUsed.

Boolean gSpatialDetrendIsIn FilteredSet

rSpatialDetrendIsIn FilteredSet

Set to true for a given feature if it is part of the filtered set used to detrend the background. This feature is considered part of the locally weighted lowest x% of features as defined by the DetrendLowPassPercentage.

float gSpatialDetrend SurfaceValue

rSpatialDetrend SurfaceValue

Value of the smoothed surface calculated by the Spatial detrend algorithm

SQT IsUsedBGAdjust 1 = Feature used 0 = Feature not used

A boolean used to flag features used for computation of global BG offset

SQT gBGUsed rBGUsed gBGSubSignal = gMeanSignal - gBGUsed

Background used to subtract from the MeanSignal; variable also used in t-test. To display the values used to calculate this variable using different background signals and settings of spatial detrend and global background adjust, see Table 34 on page 256.

* SQT Specialized Quantitation Type

Table 29 Feature results (Full) contained in the MAGE-ML (FEATURES table)

Quant Type

Features (Green) Features (Red) Options Description

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Table for Compact Output Package

This table contains only those columns required by Resolver, GeneSpring, CGH Analytics and Chip Analytics.

In the Compact version of the MAGE- ML file, the entire FEPARAMS section is included. MAGE- ML has a rich mechanism for describing protocols and protocol parameters.

Table 30 Feature results (Compact) contained in the MAGE-ML (FEATURES table)

Quant Type

Features (Green) Features (Red) Options Description

Ratio LogRatio (base 10)

-4

4

0

log(REDsignal/GREENsignal) per feature (processed signals used to calculate log ratio)

If SURROGATES are turned off, then:

if DyeNormRedSig <= 0.0 & DyeNormGreenSig > 0.0

if DyeNormRedSig > 0.0 & DyeNormGreenSig <= 0.0

if DyeNormRedSig <= 0.0 & DyeNormGreenSig <= 0.0

SQT* X_IMAGE_POSITION

Y_IMAGE_POSITION

float Found coordinates of the feature centroid in microns

MAGE-ML (XML) File Results 4 Table for Compact Output Package

Feature Extraction Reference Guide 219

Error LogRatioError

1000

If SURROGATES are turned off, then:

if DyeNormRedSig <= 0.0 OR DyeNormGreenSig <= 0.0

IF SURROGATES are turned on, then:

LogRatioError = error of the log ratio calculated according to the error model chosen

PValue PValueLogRatio Significance level of the Log Ratio computed for a feature

Derived Signal

Green.DerivedSignal Red.DerivedSignal The propagated feature signal, per channel, used for computation of log ratio

Error Green.ProcessedSig Error

Red.ProcessedSig Error

Standard error of propagated feature signal, per channel

Measured Signal

Green.Measured Signal

Red.Measured Signal

Raw mean signal of feature in green (red) channel

SQT gMedianSignal rMedianSignal Raw median signal of feature in green (red) channel

SQT gBGMedianSignal rBGMedianSignal Median local background signal (local to corresponding feature) computed per channel

Error Green.BGPixSDev Red.BGPixSDev Standard deviation of all inlier pixels per Local BG of each feature, computed independently in each channel

SQT gIsSaturated rIsSaturated 1 = Saturated or 0 = Not saturated

Integer indicating if a feature is saturated or not. A feature is saturated IF 50% of the pixels in a feature are above the saturation threshold.

Table 30 Feature results (Compact) contained in the MAGE-ML (FEATURES table)

Quant Type

Features (Green) Features (Red) Options Description

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SQT gIsLowPMTScaledUp rIsLowPMTScaledUp 1 = Low

0 = High

For XDR features, this is an integer indicating if the low PMT value was used for the calculations, or the high value.

SQT gIsFeatNonUnifOL rIsFeatNonUnifOL g(r)IsFeatNonUnifOL = 1 indicates Feature is a non-uniformity outlier in g(r)

Integer indicating if a feature is a NonUniformity Outlier or not. A feature is non-uniform if the pixel noise of feature exceeds a threshold established for a uniform feature.

SQT gIsBGNonUnifOL rIsBGNonUnifOL g(r)IsBGNonUnifOL = 1 indicates Local background is a non-uniformity outlier in g(r)

The same concept as above but for background

SQT gIsFeatPopnOL rIsFeatPopnOL g(r)IsFeatPopnOL = 1 indicates Feature is a population outlier in g(r)

Boolean flag indicating if a feature is a Population Outlier or not. Probes with replicate features on a microarray are examined using population statistics.

A feature is a population outlier if its signal is less than a lower threshold or exceeds an upper threshold determined using a multiplier (1.42) times the interquartile range (i.e., IQR) of the population.

SQT gIsBGPopnOL rIsBGPopnOL g(r)IsBGPopnOL = 1 indicates local background is a population outlier in g(r)

The same concept as above but for background

SQT gBGSubSignal rBGSubSignal gBGSubSignal = gMeanSignal - gBGUsed

Background-subtracted signal

To display the values used to calculate this variable using different background signals and settings of spatial detrend and global background adjust, see Table 34 on page 256.

Table 30 Feature results (Compact) contained in the MAGE-ML (FEATURES table)

Quant Type

Features (Green) Features (Red) Options Description

MAGE-ML (XML) File Results 4 Table for Compact Output Package

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SQT IsManualFlag Boolean flag that describes if the feature centroid was manually adjusted.

SQT gIsPosAndSignif rIsPosAndSignif g(r)isPosAndSignif = 1 indicates Feature is positive and significant above background

Boolean flag, established via a 2-sided t-test, indicates if the mean signal of a feature is greater than the corresponding background (selected by user) and if this difference is significant. To display variables used in the t-test, see Table 34 on page 256.

SQT gIsWellAboveBG rIsWellAboveBG Boolean flag indicating if a feature is WellAbove Background or not

Feature passes g(r)IsPosAndSignif and additionally the g(r)BGSubSignal is greater than 2.6*g(r)BGSDUsed.

* SQT Specialized Quantitation Type

Table 30 Feature results (Compact) contained in the MAGE-ML (FEATURES table)

Quant Type

Features (Green) Features (Red) Options Description

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Helpful hints for transferring Agilent output files

XML output

There are several situations you should be aware of as you use MAGE- ML (XML) output with gene expression data analysis software from Rosetta BioSoftware (Rosetta Resolver software):

If there is no barcode

If there is no barcode in the original .tif file for whatever reason, there will be no barcode information in the MAGE- ML output (warning message in Project Run summary). For the data to load into Rosetta Resolver, it must have a barcode associated with it. You can add barcode information in the Scan Image Properties dialog box. See the Feature Extraction 12.2 User Guide.

Access control list (ACL)

Rosetta Resolver knows about the access control list (ACL) assigned to the scan and can easily recognize and load any MAGE- ML file. The owner of the data sets the chip and hybe access controls in Rosetta Resolver before importing the profile (scan) data. For autoimport, the profile is normally placed in the MAGE directory.

XML Control Type output

If a feature is used in dye normalization, its Control_Type is normalization, even though it can also be a positive or negative control. If a feature is not used in normalization, it is either positive, negative, deletion, mismatch, or false.

MAGE-ML (XML) File Results 4 XML output

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*Not ProbeThese features are feature extracted, but they are not used by Feature Extraction as input to any calculations; these features are not used during outlier analysis or for the dye normalization calculation. However, dye normalization values and ratios are calculated, and the results appear in the text and XML output files, and the feature extraction visual results file. An exception is that Not Probes background is used in the calculation of the local background with the radius method.

Conversion of feature flag information

Failed (MAGE- ML) produce the following settings:

Bit 8 (green) and 12 (red) are set if the feature is saturated in both channels.

Bit 18 is set if the feature, or its deletion control, is a non- uniformity outlier in either color, or if the feature is a population outlier in either color and the Report Population Outliers as Failed in MAGE- ML file option is set to True.

Bit 23 is set if the probe is low specificity, e.g., when the deletion control is greater than or equal to the feature.

Table 31 Control Type Definitions

Name XML

Probe false

Positive Control pos or positive

Negative Control neg or negative

Not Probe* notprobe

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TIFF Results

You can transfer the original TIFF file or a JPEG file to Rosetta Resolver or a third- party program. The shape file, .shp, created during Feature Extraction cannot be displayed by any program other than Agilent Feature Extraction software.

TIFF file format options

See the Feature Extraction 12.2 User Guide for more information on the File Info dialog box.

Feature Extraction supports the TIFF file format. All file information for each file is listed in the File Info dialog box. The TIFF file is compliant with Adobe version 6.0 file format.

There are two sets of custom TIFF tags in the Agilent file format.

Genetic Analysis Technology Consortium (GATC) TIFF Tags Agilent Technologies is not a member of GATC or otherwise connected to this organization, and makes no internal use of these tags. They are included for the convenience of customers who use software that requires them.

Custom TIFF Tags Agilent Technologies uses its own custom TIFF tags for storing additional file information.

TIFF Tag 37701 This tag points to a data structure. This data structure is not public, but information stored in the data structure is available to customers in the MATLAB file format.

TIFF Tag 37702 This tag points to a string containing the file description. The usual TIFF description tags (tag 270) are used to hold the color name, red or green, for each image. This allows programs that interpret only standard TIFF tags to determine image colors. The Page Name tag (tag 285) also contains the color names.

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5 How Algorithms Calculate Results

Overview of Feature Extraction algorithms 226

XDR Extraction Process 236

How each algorithm calculates a result 240

Example calculations for feature 12519 of Agilent Human 22K image 292

This chapter shows you how each Feature Extraction algorithm uses its parameters to calculate results that are passed on to the next algorithm and finally on to third- party data analysis programs.

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Overview of Feature Extraction algorithms

Protocol step algorithms operate similarly during the Feature Extraction process for 2- color gene expression, CGH, ChIP, and non- Agilent microarrays. That is, the algorithms and parameter fields are similar, but the parameter values are different depending on the protocol.

The Feature Extraction process for 1- color gene expression microarrays includes only seven protocol steps, and for miRNA analysis the process includes those seven steps plus a MicroRNA Analysis step.

The examples used are primarily for 2- color microarrays. Any differences in algorithms and functions for other microarray experiments are also explained.

Algorithms and functions they perform

Place Grid

This algorithm finds the grid to define the nominal positions of the spots on the microarray.

For more information on the algorithms for XDR extraction, see XDR Extraction Process on page 236.

eXtended Dynamic Range (XDR) extraction For an XDR extraction, the grid placement is done using the high intensity scan (i.e., higher PMT voltage). The grid found using the high intensity scan is used as the starting point for the remaining extraction of both the high and low intensity images.

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Optimize Grid Fit

This algorithm improves the grid fit on the entire microarray. Leveraging from the Spot Finder algorithm, this protocol step examines the spots in the four corners of the microarray and iteratively adjusting the grid for a better fit.

If the grid has been optimized by this protocol step, the STATS table shows the stat GridHasBeenOptimized with boolean of 1; or a boolean of 0 if the grid has not been optimized.

Find Spots

This algorithm locates the exact size and centroid of each spot on the scanned microarray. Once the spot centroids have been located, the CookieCutter algorithm or WholeSpot algorithm defines the feature for each spot. The software then defines the local background for each spot based on the radius of a circle drawn around the spot.

Next, the pixel outlier algorithm identifies outlier pixels in the feature and in the local background for each spot. These pixels are then omitted from further calculations. This is the only point where data is omitted. Subsequent outlier analyses flag data, but do not remove the data.

Inlier pixels within the cookie area represent a feature while the inlier pixels within the annulus around the feature, after excluding the exclusion zone, represent the local background.

NOTE With version 10.x and higher of the software, you no longer have to perform XDR dual scans or extractions to capture the full dynamic range of the data. You can get the same dynamic range by working with the 20-bit TIFF Dynamic Range option. This option is meant to be a replacement for the XDR option. You capture the full dynamic range with better accuracy.

Choosing the XDR option may still be useful if you want to compare XDR data from the G2565BA Scanner with XDR data from the G2565CA Scanner.

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The Feature Extraction program calculates the following values from these inlier pixels: mean, median, standard deviation, normalized IQR, and number of inlier pixels.

XDR extraction This is the only step that is run twice on an XDR extraction. The spot placement and spot measurements are found separately for the high and low intensity scans. Then the XDR algorithm decides on a feature by feature basis which scan the data should come from (more on this follows). For features that are very bright in the high intensity scan, the XDR algorithm uses the data from the low intensity scan. This choice is made independently for each color channel.

For each feature that uses data from the low intensity scan, the following columns get replaced (determined separately for red and green channels): NumPixOLHi, NumPixOLLo, NumPix, MeanSignal, MedianSignal, PixSDev, PixNormIQR, NumSatPix, IsSaturated, NetSignal.

These columns include the raw data from the spotfinding and measurement steps (signal levels, pixel noise levels, number of pixels, if the pixels and feature are saturated). Once the substitutions have been made to some features in each color channel, the extraction proceeds as if there were only a single combined set of features.

Flag Outliers

Next, the Flag Outliers algorithm flags anomalous features and local backgrounds as non- uniformity outliers and/or population outliers. Population outlier flagging is based on population statistics of replicate features on the microarray.

Which of two statistical tests is used to identify population outliers depends on the number of replicate features on the microarray.

Non- uniformity outlier flagging is based on statistical deviation from the expected noise in the Agilent microarray- based system (scanner, labeling/hybridization protocols, and microarrays). The algorithm automatically

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calculates the B (linear) and C (constant) terms of the polynomial fit for the expected noise for any type of microarray experiment.

Compute Bkgd, Bias and Error

This algorithm applies background subtraction to each feature to yield the background- subtracted intensity. You can also apply a spatial detrend algorithm to estimate and remove noise due to a systematic gradient on the microarray.

Another algorithm can correct for any underestimation or overestimation of the background in both the red and green channels of low- intensity signals by applying a global background adjustment value to the background- subtracted signals.

Before using the algorithm for estimating the error, the system uses an algorithm to calculate robust negative control statistics for both CGH and miRNA data.

CGH microarrays have a variety of sequences that are used as negative controls. Occasionally, hot features are not flagged as population outliers. In addition, hot sequences may exist; that is, all features of that sequence have higher signals than features in other negative control sequences. These problems can inflate NegC SD, which is used in the calculation of AdditiveError for the CGH error model.

To provide an estimate of the error in the background- subtracted signal calculation, the error model is now calculated after background subtraction. The 1- color error model has been changed to exactly mimic the 2- color error model.

To determine if the feature intensity is significant compared to the background intensity, two kinds of tests are available: t- test and WellAboveBG test. Both of these tests depend upon an estimation of background error.

The default protocol for older Agilent protocols still uses pixel statistics of local background regions to estimate background error in the 2- sided t- test. Newer Agilent

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protocols use an improved estimation of background error: the additive error, calculated from the Agilent error model. You can choose between these two background error estimations in the protocol parameter field, Significance (for IsPosAndSignif and IsWellAboveBG).

The WellAboveSDMulti confidence test is used to determine if the feature background- subtracted signal is well above its background error.

Surrogates are calculated here and depend on the significance model used. Given the standard t- test, the surrogates are calculated exactly as before. Given the new significance test based upon additive error, the surrogate value is determined by the additive error and the p- value.

The program can also use a multiplicative detrend algorithm, if selected or the default in the protocol, to provide a surface fit to account for the dome effect that can happen when microarrays are processed.

Placing the error model calculation step before the significance calculation permits the result of the error model calculation to be used for the significance calculation, surrogate calculation and multiplicative detrending steps.

Correct Dye Biases

Since dye bias between the red and green channels is a common phenomenon in a dual- color microarray platform, this algorithm adjusts for the bias by multiplying the background- subtracted signals with the appropriate dye normalization factors. Both linear and non- linear (locally weighted) normalization methods are available.

Surrogates are applied after the dye norm fit and before the dye normalization takes place. This ensures that only real data contribute to the fit and also surrogate data is correctly dye- normalized for both the Linear and Lowess options.

Because 1- color experiments use only the green channel, they do not use this protocol step. Surrogates exist and can be used for 1- color.

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Compute Ratios

This algorithm determines if a feature is differentially expressed by calculating the log ratio of the red over green processed signals. The processed signal is the dye- normalized signal.

Because 1- color experiments use only the green channel, they do not use this protocol step.

MicroRNA Analysis

This step is used in the 1- color miRNA analysis after background effects have been accounted for. The algorithms in this step calculate the TotalGeneSignal, the TotalGeneError, The GeneSignal, and the ProbeRatio for the analysis.

Calculate Metrics

These algorithms calculate all the QC metrics for the analysis. One of the primary algorithms in this step is the gridding test, whose parameter values are hidden in the protocol. This algorithm yields grid warnings on the Summary Reports and the Evaluate Grid warning in the QC Report. Agilent has added many more tests to assess if gridding has been successful or not.

Protocols for Agilent arrays also have associated QC metric sets. These metrics are calculated at this step.

Agilent miRNA protocols also have specialized metrics calculated at this step.

Generate Results

This part of the process generates the output result files using the parameter values specified in the protocol step and the selections made in the Project Properties window. This step is not discussed in this chapter.

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Algorithms and results they produce

Table 32 summarizes the results for each algorithm (protocol step). These result names are used in the equations for the calculations for each algorithm.

Table 32 Algorithms (Protocol Steps) and the results they produce

Protocol Step Results Result Definition

Find Spots MeanSignal Average raw signal of feature calculated from the intensities of all inlier pixels that represent the feature (after outlier pixel rejection). The number of inlier pixels is shown in the column NumPix.

Find Spots MedianSignal Median raw signal of feature calculated from the intensities of all inlier pixels that represent the feature (after outlier pixel rejection). The number of inlier pixels is shown in the column NumPix.

Find Spots BGMeanSignal Average raw signal of the local background calculated from intensities of all inlier pixels that represent the local background of the feature (after outlier pixel rejection). The number of inlier pixels is shown in the column BGNumPix.

Find Spots BGMedianSignal Median raw signal of the local background calculated from intensities of all inlier pixels that represent the local background of the feature (after outlier pixel rejection). The number of inlier pixels is shown in the column BGNumPix.

Find Spots NetSignal MeanSignal minus Dark Offset

Find Spots IsSaturated A Boolean flag of 1 indicates that the feature is saturated; at least 50% of the inlier pixels in the feature have intensities above the saturation threshold. One can determine the saturation level of a feature by dividing the NumSatPix by the NumPix.

Flag Outliers IsFeatureNonUnifOL A Boolean flag of 1 indicates that the feature is a non-uniformity outlier; the measured feature pixel variance is greater than the expected feature pixel variance plus the confidence interval.

Flag Outliers IsFeatPopOL A Boolean flag of 1 indicates that the feature is a population outlier. This means that the feature MeanSignal is greater than the upper rejection boundary or less than the lower rejection boundary, both of which are determined by multiplying a factor (1.42) by the interquartile range of the population, made up of intra-array feature replicates. (See Step 6. Reject outliers on page 247.)

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Compute Bkgd, Bias and Error

BGAdjust An adjustment value added to the initial background-subtracted signal to correct for underestimation or overestimation of the background. This value can be positive or negative. Note the BGAdjust values are reported per channel in the STATS table of Feature Extraction text file.

Compute Bkgd, Bias and Error

BGused Final background signal used to subtract the background from the feature mean signal. To view the values used to calculate this variable using different background signals and settings of spatial detrend and global background adjust, see Table 34 on page 256.

Compute Bkgd, Bias and Error

BGSubSignal Feature signal after subtraction of the background corrections. To view the values used to calculate this variable using different background signals and settings of spatial detrend and global background adjust, see Table 34 on page 256.

Compute Bkgd, Bias and Error

IsPosAndSignif If significance is based on pixel statistics, a Boolean flag of 1 indicates that the feature MeanSignal is greater than and significant compared to the background signal (i.e BGUsed).

If significance is based on the Additive Error of the Error Model, a Boolean flag of 1 means that the feature MeanSignal is greater than and significant compared to the Additive Error,

Compute Bkgd, Bias and Error

IsWellAboveBG A Boolean flag of 1 indicates that the feature BGSubSignal is well above background and passes the IsPosAndSignif test.

Compute Bkgd, Bias and Error

SpatialDetrendIsIn FilteredSet

Set to true for a given feature if it is part of the filtered set used to detrend the background. The feature may be in the set of locally weighted lowest x% of features as defined by the DetrendLowPassPercentage, may be a negative control feature or may be part of the set of features that are in the negative control range. The feature set is defined by the detrend method selected.

Compute Bkgd, Bias and Error

SpatialDetrend SurfaceValue

Value of the smoothed surface, at that feature, calculated by the Spatial detrend algorithm

Table 32 Algorithms (Protocol Steps) and the results they produce (continued)

Protocol Step Results Result Definition

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Compute Bkgd, Bias and Error

MultDetrendSignal A surface is fitted through the log of the background-subtracted signal to look for multiplicative gradients. A normalized version of that surface interpolated at each point of the microarray is stored in MultDetrendSignal. The surface is normalized by dividing each point by the overall average of the surface. That average is stored in MultDetrendSurfaceAverage as a statistic.

If the protocol uses the option to fit to only replicate features, the surface is normalized for the fit. The MultDetrend SurfaceAverage is smaller in this case, a number around 1.

Compute Bkgd, Bias and Error

SurrogateUsed A non-zero surrogate value indicates that the MeanSignal is less than or not significant versus the background or the BGSubSignal is less than the Error, where the Error is the Additive Error for all default Agilent Protocols.

Correct Dye Biases DyeNormSignal A dye-normalized signal calculated by multiplying the BGSubSignal with the appropriate DyeNormFactor.

Correct Dye Biases LinearDyeNormFactor (Table 17 on page 129)

A global constant to normalize the dye bias from all feature background-subtracted signals. LinearDyeNormFactor is calculated such that geometric mean intensity of the selected normalization features equals 1000.

Compute Ratios ProcessedSignal The signal left after all the Feature Extraction processing steps have been completed. In the case of 1-color, ProcessedSignal contains the Multiplicatively Detrended BackgroundSubtracted Signal if the detrending is selected and helps. If the detrending does not help, this column will contain the BackgroundSubtractedSignal.

Compute Ratios ProcessedSigError The universal or propagated error left after all the processing steps of the Feature Extraction process have been completed. In the case of one color,

If multiplicative detrending is performed, ProcessedSignalError contains the error propagated from detrending. This is done by dividing the error by the normalized MultDetrendSignal.

Compute Ratios LogRatio Log of the ratio of rProcessedSignal over gProcessedSignal. The log ratio indicates the level of gene expression in cyanine 5-labeled sample relative to cyanine 3-labeled sample.

Table 32 Algorithms (Protocol Steps) and the results they produce (continued)

Protocol Step Results Result Definition

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Compute Ratios pValueLogRatio P-value indicates the level of significance in the differential expression of a gene as measured through the log ratio.

MicroRNA Analysis gTotalGeneSignal This signal is the sum of the total probe signals in the green channel per gene.

MicroRNA Analysis gTotalGeneError This error is the square root of the sum of the squares of the TotalProbeError.

Table 32 Algorithms (Protocol Steps) and the results they produce (continued)

Protocol Step Results Result Definition

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XDR Extraction Process

What is XDR scanning?

The Agilent scanner can cover a dynamic intensity range greatly in excess of the range covered by a single scan. Furthermore, Agilent microarray features can produce signals that span a broader range of intensity than a single scan can cover. Therefore, you can use eXtended Dynamic Range (XDR) to cover the full dynamic intensity range of your microarray features and hence see the most useful biology.

To do this you set the scanner to scan twice, once at a high PMT setting (the high intensity scan) followed immediately by a low PMT setting (the low intensity scan). This functionality is enabled using Agilent Scan Control Software version 7.0. The two scans are labeled in their tiff headers as paired scans of the same microarray.

XDR Feature Extraction process

The Feature Extraction program (v9.1 and later) uses this information to know to extract the low and high PMT images as a pair. In this XDR extraction type, the Feature Extraction program processes the two scans together and produces a single set of outputs that contain data from both scans.

Some of the features contain data from the high intensity scan and some from the low intensity scan. You can determine this by viewing the column, r,gIsLowPMTScaledUp, for each color channel. For signals that are very bright (or saturated) in the high intensity scan (e.g., a scan at 100% PMT gain), the XDR algorithm substitutes the data from the low intensity scan (e.g., 10% PMT gain) after scaling the intensity appropriately.

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To extract these arrays, the Feature Extraction program uses a somewhat different flow of the image processing and data analysis algorithms.

The Feature Extraction program places the grid on the high intensity scan only, then finds spots using this grid on each of the two scans.

The XDR algorithm decides which features should use the low intensity scan data, scales these signals appropriately and does a replacement for each feature and color channel where appropriate. Then Feature Extraction proceeds with the rest of the data analysis (outlier detection, background correction, dye normalization, etc.) exactly as it would for a single non- XDR scan.

Upon completion, the Feature Extraction program generates results as if they were from a single measurement of the microarray. The QC report and the stats table indicate that the Feature Extraction program extracted an XDR image pair by stating the new saturation value. This is the saturation value of the low intensity scan after suitable scaling. For instance, if the high intensity scan is at 100% and the low intensity scan is at 10%, the new saturation values will be around 650,000 (about 10x greater than a normal 100% PMT gain scan). This lets you use data in your calculations covering a much greater dynamic range.

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How the XDR algorithm works

How does the XDR algorithm decide how to combine and scale the data from the high intensity and low intensity scans? The general theory is that the high intensity gives the best results for the low end of the signal range and the low intensity scan gives better data for bright features (less affected by saturation). The Feature Extraction program uses a signal level of 20,000 as the cut- off between the two scans. If the NetSignal of the high intensity scan is greater than 20,000 counts, then the data from the low intensity scan is used.

The low intensity scan is scanned with a lower PMT gain than the high intensity scan (say 10% versus 100%). So to combine the data, the signals from the low intensity scan must be increased to match those from the high intensity scans.

To determine the factor by which the low- intensity signal should be scaled, the algorithm uses features that have signals in an overlap range where both the high and low intensity scans provide very stable data. This range is Net Signals in the high intensity scan greater than 300 counts and less than 20,000 counts.

Using data in this range, the Feature Extraction program generates a linear fit (with a slope and an intercept) that transforms the low- intensity mean signals into the same range as high intensity scans. The final scaled signal for the XDR extraction is MeanSignal ([low- intensity scan * slope] + intercept).

The linear fit constants determined in this step are included in the stats table.

For signals over 20,000 counts in the high intensity scan, therefore, the low intensity scan signals can extend to nearly 1.2 million counts.

If the low intensity scan has a spot centroid too far from the high intensity centroid (greater than 2 pixels), the algorithm does not make a substitution.

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Troubleshooting the XDR extraction

The XDR algorithm provides warnings in the project summary report to indicate an issue with the XDR extraction process.

No XDR signal substitution for color red/green.

This message appears if there are no features for which the low intensity data are substituted. This could occur on a dim array

Computation of the XDR fit for red/green is based on only X pairs of (high PMT, low PMT) matching values.

This message appears if very few features had data in the overlap range for the fit. The user should check the data in this case to confirm that the XDR combination is satisfactory.

Computation of the XDR fit for red/green results in a large intercept.

This message appears if the linear fit between the low and high intensity scans has a very large intercept.

This can be indicative of a poor linear fit. The user should check the data in this case to confirm that the XDR combination is satisfactory.

Computed XDR ratio for red/green is X vs. expected Y from PMT settings. Check scanner calibration.

This message appears if the ratio of the high/low intensity scans is different from what is expected from the scanner. For instance, an XDR scan set with 100% and 10% for PMT gain settings should yield a ratio close to 10.

If this ratio is different than expected, the Feature Extraction program may or may not have performed correctly. But you should check the data in this case to confirm that the XDR combination is satisfactory.

This message is more likely to appear as the low intensity PMT gain setting gets closer 1%. This is because the percentage error in the PMT gain setting increases as the setting moves away from 100%.

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How each algorithm calculates a result

Place Grid

Step 1. Place a grid to find the nominal spot positions

After the Feature Extraction program automatically determines the format of the grid, it initiates the next steps.

The algorithm reduces the two- dimensional image data of the microarray to two one- dimensional data sets that are further processed to determine the layout of the grid on the microarray.

Projection of the two- dimensional microarray is performed to produce two one- dimensional data sets (projected signals). From the one- dimensional data sets, peaks of the projected signals are filtered to determine which peaks to retain for further processing, based on predetermined peak height and peak width thresholds.

Nominal spacing between the features may be estimated based on a statistical determination of a most frequent distance between centers of retained peaks that are adjacent to one another. Coordinates for the features on the microarray, relative to the X and Y axes, are generated based on the selected peaks and peak spacing. The grid is then adjusted for rotation and skew.

NOTE In Feature Extraction 12.1, an enhanced gridding algorithm was released and used in the default CGH protocol. The enhancements include a new iterative method for determining grid position, rotation, and skew, and several fine grid tuning methods that improve the calculation of rotation and skew. Enhanced gridding also uses both the foreground and background of the corner stencil patterns to improve identification of grid corners.

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The background peak shift flag helps to improve the gridding. Ideally, all background pixels should have a gray value of zero. In practice these values are nonzero.

When this flag is set to true, the algorithm determines the background pixels pixel value from the histogram of the image. All pixels having a non- zero value (background +/- window) are set to zero, thus reducing the contribution of background pixels in the two one- dimensional projected signals. This shift in the peak of the background signal leads to better determination of peaks.

The following figures illustrate the result of applying Background Peak Shifting. Figure 50 is a histogram of a typical 30 micron feature array before Background Peak Shifting. Figure 51 depicts the same array after applying Background Peak Shifting. Note that this operation is done internally in the grid placement algorithm. The actual image data remains unchanged. Some variations in the results are expected with and without use of this flag as the grid positions obtained differ.

Figure 50 Histogram of a 30 micron feature array image. The X-axis cor- responds to the pixel value and the Y-axis to the frequency of occurrence.

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Figure 51 Zoomed in section of Figure 50. The background peaks are at 32 for the red channel and 50 for the green channel.

Figure 52 Histogram of a 30 micron feature array image after Back- ground Peak Shifting.

Figure 53 Zoomed in section of Figure 52. Note the peaks at pixel val- ue=0. Also note the dips in the frequency of values near the pixel value of 32 for the red channel and 50 for the green channel.

When the Use central part of pack for slope and skew calculation flag is set to True, the gridding algorithm is modified to use central region of the pack to obtain slope, skew and origin of each pack, instead of using the edges of packs. This enables the algorithm to correctly place the grid for arrays that have edges populated with dim spots.

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When the Use the correlation method to obtain origin X of subgrids is set to False, results obtained from the projection data analysis are used to estimate the origin. Selecting this option will use the same calculations used in Feature Extraction version 10.7/10.9 or earlier. When the flag is set to True, the software performs one extra step of correlation following the projection data analysis to get the origin. This option is of use particularly in cases where pack edges have dim spots and are failing to grid.

Optimize Grid Fit

Step 2. Iteratively adjust grid by examining the corner spots

This algorithm improves the grid fit by leveraging from the Spot Finder algorithm. Looking only at the specified square area of features at each corner of the microarray, it performs the iteratively adjust corners method up to the maximum number of iterations specified in the protocol. It adjusts the grid only if the following criteria are met.

The absolute average difference between the grid position and the spot position is within the specified Adjustment Threshold.

The number of features considered found by the spot finder algorithm is within the specified Found Spot Threshold.

Find Spots

Step 3. Locate the spot centroids

The calculation is based on an iterative Bayesian- probability- based pixel classification. A binary feature mask is created that classifies the pixels in a region of interest around each grid position into feature pixels or background pixels. The approximate radius of each feature mask is

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considered as the corresponding spot radius and the center of mass of the feature mask is considered as the actual spot centroid.

In the visual results view (.shp file), all spots that are found are shown using a blue X on the spot and marked as Found. For all spots, the blue cross (+) shows the location of the grid. If the centroid cannot be found because the spot is too weak, or the distance between + and X centroids exceeds the range specified by the Spot Deviation Limit, this spot is labeled Not Found.

For CGH protocols in which the Use Enhanced SpotFinding option is set to True, the algorithm increases the size of the window around the expected spot centroids in which it looks for pixels to assign to each spot. This larger window allows for improved identification of all of the spot pixels. The algorithm removes any pixels within that increased window size that are attributable to neighboring spots. The result is that fewer features are called as non- uniform.

Step 4. Define features

See the Feature Extraction 12.2 User Guide for how the Feature Extraction program defines features either with the CookieCutter method or the WholeSpot method.

Step 5. Estimate the radius for the local background

The radius is the distance from the center of the cookie or whole spot to the edge of the outermost region, as shown in Figure 54. The default radius is the value specified in the protocol. You can also enter a minimum radius whose value is less than the default radius, or you can enter a larger radius to capture more pixels in the background. You can use the radius method for estimating global backgrounds as well.

The figures in this step represent the local background for the CookieCutter method for defining features. The radius for the local background is estimated in the same way for the WholeSpot method.

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Figure 54 Local background in relation to other zones for CookieCutter method

Default radius The default radius is the radius of the local background for one feature. This radius is known as the SELF radius and its value is the default value that you see in the Find and Measure Spots protocol step if autoestimation is turned off.

Although the radius can map a circle that appears to overlap other features, the Feature Extraction program does not use these pixels to calculate the local background signal.

Figure 55 Example of a SELF radius

The value of the default radius (in microns) depends on the scan resolution and interspot spacing found in the TIFF and grid template or file, shown in equation [1]:

For the WholeSpot method, if extraction stops at this step, you may need to enter a larger radius than the protocol default radius.

The software autoestimates the Default Local Radius if specified in the protocol. Otherwise, you can enter this radius in the Feature Extraction Protocol Editor.

Feature or cookie

Exclusion zone

Local background

Default Local Radius = SELF = (0.6 x Scan_resolution x Max (Interspotspacing_x, Interspotspacing_y)) [1]

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Minimum radius The minimum radius that you can enter is the FLOOR (Default Radius), where FLOOR rounds the calculated value of the default radius down to the next lower integer, e.g., FLOOR (87.6) = 87.

Maximum radius The software lets you enter a maximum radius for the local background no greater than the distance from the center of the innermost feature to the edge of a circle that approximately surrounds the fourth closest set of nearest neighbors, or n=4, as shown in Equation 2. The set of eight nearest neighbors closest to the feature of interest is defined as n=1, as shown in Equation 3.

Figure 56 Example of the radius for the first closest set of nearest neighbors, or n=1 (eight nearest neighbors)

The value of the maximum radius also depends on the scan resolution and interspot spacing in the TIFF and grid template or file, shown in the equation.

where CEILING rounds the calculated value up to the next higher integer, e.g., CEILING [3.2] = 4.

Any radius The value of any radius between the minimum and maximum that circumscribes a circle surrounding the nth closest set of nearest neighbors from the central spot can be approximated as:

Max radius = CEILING [(Scan_resolution x 4.7) [2]Interspotspacing_x 2 Interspotspacing_y 2+

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where n=1,2,3 or 4. Figure 57 shows the set of nearest neighbors where n = 2.

Figure 57 Example of the radius for the second closest set of nearest neighbors, or n=2

Step 6. Reject outliers

The calculation to determine the boundaries for rejection of the outlier pixels is defined in the following equations and diagram.

Assumptions for default value of 1.42 The following assumptions lead to the default value of 1.42 for this parameter.

Normal distribution for pixel intensity, where y- axis corresponds to pixel frequency and x- axis corresponds to pixel intensity.

A 99% confidence interval that the pixels of interest are contained within the boundaries for rejection.

Radius_n = Scan_resolution x n.6 [3]Interspotspacing_x 2 Interspotspacing_y 2+

24 nearest neighbors

(n = 2) 2

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The Interquartile Range (IQR) is the range of points under a Gaussian

distribution contained between the 25th percentile mark (25% of the

points are contained under the curve from the zero point to the

25th percentile mark) and the 75th percentile mark. The 50th

percentile mark is coincident with the median of the curve.

The boundary for rejection is the point on the x-axis beyond which

all pixels will be rejected.

D is the distance between the mean of the curve and the

boundary for rejection.

Calculations of default value The following calculations are based on the above assumptions.

If a pixel is located within the 99% confidence interval, it is 2.6 standard deviations (SD) away from the mean. Or, D = 2.6*SD and .

From the Z table for cumulative normal frequency distribution, the ZP=0.75 = 0.675.

Therefore, SD = IQR/2

If you combine the four equations above and solve for the Mult_factor, the Mult_factor = 1.42.

If you would rather use a 95% confidence interval, IQR Mult_factor = 0.952. The reason for this is, assuming normal distribution and infinite degrees of freedom, D = 1.96 * SD = .

Figure 58 Important points on Gaussian curve# of pixels vs. intensity

Step 7. Calculate the mean signal of the feature (MeanSignal)

The intensities of inlier pixels of a feature are averaged to give mean signal of the feature before background subtraction. The NumPix column in the result file lists the number of inlier pixels in the cookie that remain after rejection of outlier pixels.

_ IQRfactorMultD

675.0

IQR95185.0