Thermo Fisher Scientific GeneMapper® ID-X Software Owner's Manual

Below you will find brief information for GeneMapper ID-X Software Version 1.0. This guide explains how to perform AmpFlSTR kit data analysis using the GeneMapper ID-X Software Version 1.0 to aid in the interpretation of samples.

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Getting Started Guide
GeneMapper&reg; ID-X Software
Version 1.0
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Getting Started Guide
Getting Started
GeneMapper&reg; ID-X
Software
Setting Up the
Software
Version 1.0
Creating a
Project,
Analyzing, and
Reviewing
Analysis Workflow
Summaries
Manually
Reviewing and
Interpreting Data
Performing
Quality Control of
Sample Results
Performing
Peer/Technical
Review of
Electronic Data
Reporting,
Exporting and
Printing Results
&copy; Copyright 2007, Applied Biosystems. All rights reserved.
For Research, Forensic, or Paternity Use Only. Not for use in diagnostic procedures.
Information in this document is subject to change without notice. Applied Biosystems assumes no responsibility for any errors that
may appear in this document.
GeneMapper&reg; ID-X Software has undergone a verification process defined by Applied Biosystems. However, human identification
laboratories analyzing forensic, paternity, databasing and single-source samples that choose to use GeneMapper ID-X Software for
data analysis should perform their own appropriate validation studies.
APPLIED BIOSYSTEMS DISCLAIMS ALL WARRANTIES WITH RESPECT TO THIS DOCUMENT, EXPRESSED OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THOSE OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR
PURPOSE. IN NO EVENT SHALL APPLIED BIOSYSTEMS BE LIABLE, WHETHER IN CONTRACT, TORT, WARRANTY,
OR UNDER ANY STATUTE OR ON ANY OTHER BASIS FOR SPECIAL, INCIDENTAL, INDIRECT, PUNITIVE,
MULTIPLE OR CONSEQUENTIAL DAMAGES IN CONNECTION WITH OR ARISING FROM THIS DOCUMENT,
INCLUDING BUT NOT LIMITED TO THE USE THEREOF.
Notice to Purchaser: License Disclaimer.
Purchase of this software product alone does not imply any license under any process, instrument or other apparatus,
system, composition, reagent or kit rights under patent claims owned or otherwise controlled by Applera Corporation,
either expressly, or by estoppel.
TRADEMARKS:
Applera, Applied Biosystems, AB (Design), ABI PRISM, AmpFlSTR, GeneMapper, Genotyper, Identifiler, LIZ, SGM Plus, and
Yfiler are registered trademarks and GeneScan, ROX, and VALID are trademarks of Applera Corporation or its subsidiaries in the
US and/or certain other countries.
This product includes software developed by the Apache Software Foundation.
This product includes software developed by the ExoLab Project.
JNIRegistry is copyrighted &copy; by ICE Engineering, Inc.
Microsoft, Excel and Windows are registered trademarks of Microsoft Corporation.
All other trademarks are the sole property of their respective owners.
4375574 Rev. A
10/2007
Contents
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
How to Use This Guide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
How to Obtain More Information . . . . . . . . . . . . . . . . . . . . . . . . . . . xi
How to Obtain Support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii
Chapter 1
Getting Started . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Overview of the GeneMapper&reg; ID-X Software Version 1.0 . . . . . . . 2
Features of the GeneMapper&reg; ID-X Software . . . . . . . . . . . . . . . . . 3
Analysis Requirement Check . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Allelic Ladder Quality Assessment . . . . . . . . . . . . . . . . . . . . . . 3
Analysis Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Comprehensive Quality Value System . . . . . . . . . . . . . . . . . . . 3
Manual Review Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Quality Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Chain-of-Custody Systems for Electronic Data . . . . . . . . . . . . 4
Multi-User Database Environment . . . . . . . . . . . . . . . . . . . . . . 5
Report Manager . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
GeneMapper&reg; ID-X Software and Analysis Workflows . . . . . . . . . . 6
The GeneMapper&reg; ID-X Software Quality Value System. . . . . . . . . 7
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Optimizing and Validating an Expert System . . . . . . . . . . . . . . 7
Quality Value System Checks and Assessments . . . . . . . . . . . 8
Analysis Requirements Checks. . . . . . . . . . . . . . . . . . . . . . . . . 9
Sizing Quality Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
Allelic Ladder Quality Assessment . . . . . . . . . . . . . . . . . . . . . 10
Marker-Level Quality Assessments. . . . . . . . . . . . . . . . . . . . . 11
Genotype Quality Assessment . . . . . . . . . . . . . . . . . . . . . . . . 12
Sample-Level Quality Assessments . . . . . . . . . . . . . . . . . . . . 13
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
iii
GeneMapper&reg; ID-X Software Security . . . . . . . . . . . . . . . . . . . . . 14
GeneMapper&reg; ID-X Software Terms . . . . . . . . . . . . . . . . . . . . . . 15
How to Use This Guide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Before You Start . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
User Account Requirements. . . . . . . . . . . . . . . . . . . . . . . . . . 17
Using the Guide with the Example Data Provided . . . . . . . . . 18
Using the Guide as a Tutorial . . . . . . . . . . . . . . . . . . . . . . . . . 18
For More Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Chapter 2
Setting Up the Software . . . . . . . . . . . . . . . . . . . . . . . 21
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
In This Chapter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
Step 1: Start the Software and Log In. . . . . . . . . . . . . . . . . . . . . . 22
Starting the Software and Logging In . . . . . . . . . . . . . . . . . . . 22
Resizing and Exploring the Project Window. . . . . . . . . . . . . . 24
Exploring the Context-Sensitive Help System . . . . . . . . . . . . 24
Step 2: View Panels, Bins, and Stutter Settings . . . . . . . . . . . . . . 26
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
When to Import . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Viewing Panel, Bin, and Stutter Settings . . . . . . . . . . . . . . . . 26
Step 3: Create an Analysis Method. . . . . . . . . . . . . . . . . . . . . . . . 29
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
In This Section . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
Creating the Analysis Method. . . . . . . . . . . . . . . . . . . . . . . . . 30
Step 4: Review Default Table Settings, Plot Settings, and Size
Standards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
Review Default Table Settings . . . . . . . . . . . . . . . . . . . . . . . . 35
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
Reviewing Table Settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
Defaults Provided . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
Creating a New Table Setting . . . . . . . . . . . . . . . . . . . . . . . . . 37
Review Default Plot Settings . . . . . . . . . . . . . . . . . . . . . . . . . 40
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
Reviewing Plot Settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
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GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Defaults Provided . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
Creating a New Plot Setting . . . . . . . . . . . . . . . . . . . . . . . . . . 42
Review Default Size Standards . . . . . . . . . . . . . . . . . . . . . . . . 45
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Reviewing Size Standard Settings . . . . . . . . . . . . . . . . . . . . . 45
Defaults Provided . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Step 5: Import Lab Reference and Custom Control Profiles . . . . . 46
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
Importing the Reference Project . . . . . . . . . . . . . . . . . . . . . . . 47
Adding Profiles to the Software Database . . . . . . . . . . . . . . . 48
Viewing Profiles in the Profile Manager. . . . . . . . . . . . . . . . . . 50
Step 6: Set the Project Options . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
In This Section. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
Setting Project Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
Chapter 3
Creating a Project, Analyzing, and Reviewing Analysis
Workflow Summaries . . . . . . . . . . . . . . . . . . . . . . . . . 55
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
In This Chapter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
Step 1: Create a Project and Add Samples. . . . . . . . . . . . . . . . . . 56
Creating a New Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
Adding Samples from Sample Files . . . . . . . . . . . . . . . . . . . . 57
Step 2: View Sample Information and Raw Data. . . . . . . . . . . . . . 59
Viewing Sample Information . . . . . . . . . . . . . . . . . . . . . . . . . . 60
Viewing Raw Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
Step 3: Select Analysis Settings and Start Analysis . . . . . . . . . . . 63
Selecting Analysis Settings . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
Starting Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
Step 4: Review the ARS and Correct the Requirements . . . . . . . . 64
Reviewing the ARS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
Correcting the Analysis Requirements . . . . . . . . . . . . . . . . . . 66
Step 5: Analyze the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
Analyzing the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
v
Viewing Analysis Progress . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
Step 6: Review the Analysis Summary . . . . . . . . . . . . . . . . . . . . . 68
About the Analysis Summary Tab . . . . . . . . . . . . . . . . . . . . . 68
Features of the Analysis Summary Tab . . . . . . . . . . . . . . . . . 69
Areas of the Analysis Summary Tab. . . . . . . . . . . . . . . . . . . . 70
Chapter 4
Manually Reviewing and Interpreting Data . . . . . . . . 73
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
In This Chapter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
Step 1: Examine Allelic Ladder Quality . . . . . . . . . . . . . . . . . . . . . 74
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
Viewing Allelic Ladder Quality Status . . . . . . . . . . . . . . . . . . . 75
Examining the Low-Quality Allelic Ladder . . . . . . . . . . . . . . . 75
Step 2: Examine Control Quality . . . . . . . . . . . . . . . . . . . . . . . . . . 83
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
Viewing Control Quality Status . . . . . . . . . . . . . . . . . . . . . . . . 83
Examining a Passing Control . . . . . . . . . . . . . . . . . . . . . . . . . 84
Examining a Low-Quality Control . . . . . . . . . . . . . . . . . . . . . . 86
Step 3: Examine Sample Quality. . . . . . . . . . . . . . . . . . . . . . . . . . 88
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
Viewing Sample Quality Status. . . . . . . . . . . . . . . . . . . . . . . . 88
Examining the Low-Quality Samples . . . . . . . . . . . . . . . . . . . 89
Step 4: Review the Low-Quality Sample Results . . . . . . . . . . . . . 90
Examining the SQ Sample Results . . . . . . . . . . . . . . . . . . . . . 90
Displaying the Low-Quality Sample Plots. . . . . . . . . . . . . . . . 91
Examining the SSPK Sample Results. . . . . . . . . . . . . . . . . . . 92
Examining the MIX Sample Results . . . . . . . . . . . . . . . . . . . . 99
Examining the SQ Sample Results . . . . . . . . . . . . . . . . . . . . 102
Examining the OMR Sample Results . . . . . . . . . . . . . . . . . . 108
Step 5: View Additional Plot Settings . . . . . . . . . . . . . . . . . . . . . 129
Step 6: Delete Samples from the Project . . . . . . . . . . . . . . . . . . 133
Step 7: Save the Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
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GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 5
Performing Quality Control of Sample Results . . . . 135
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
About Quality Control of Sample Results . . . . . . . . . . . . . . . 136
In This Chapter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
Understanding the Profile Comparison Tool . . . . . . . . . . . . . . . . 137
Terms You Need to Know . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
Sample Concordance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
Sample, Lab Reference, Custom Control, and
QC Comparison . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
Step 1: Examine Sample Concordance. . . . . . . . . . . . . . . . . . . . 140
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
Examining Sample Concordance . . . . . . . . . . . . . . . . . . . . . 140
Step 2: Perform Sample Comparison and View Results . . . . . . . 141
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
Performing Sample Comparison . . . . . . . . . . . . . . . . . . . . . . 142
Viewing the Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
Step 3: Perform Lab Reference Comparison and View Results . 143
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
Performing Lab Reference Comparison . . . . . . . . . . . . . . . . 143
Viewing the Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
Step 4: Perform Control/QC Comparison and View Results . . . . 144
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
Performing Control/QC Comparison. . . . . . . . . . . . . . . . . . . 144
Viewing the Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
Chapter 6
Performing Peer/Technical Review of Electronic
Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
About Electronic Peer/Technical Review . . . . . . . . . . . . . . . 146
In This Chapter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
Step 1: View Samples with Manual Edits and Overrides. . . . . . . 146
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
Viewing CGQ Overrides . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
Viewing Edited Samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
vii
Step 2: View Edits in the Label Edit Viewer. . . . . . . . . . . . . . . . . 147
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
Viewing Edits from the Samples Plot . . . . . . . . . . . . . . . . . . 148
Viewing Edits from the Project Window . . . . . . . . . . . . . . . . 151
Exporting the Label Edit Viewer from the Project Window. . 151
Step 3: View Allele Edits and Comments in the Genotypes Table
and Genotypes Plot. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
Viewing Allele Calls in the Genotypes Table. . . . . . . . . . . . . 153
Viewing Allele Calls in the Genotypes Plot . . . . . . . . . . . . . . 153
Chapter 7
Reporting, Exporting and Printing Results. . . . . . . . 155
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156
Step 1: Create a Custom Report Setting . . . . . . . . . . . . . . . . . . 156
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156
Creating a Custom Report Setting . . . . . . . . . . . . . . . . . . . . 156
Step 2: Generate the Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
Step 3: Export the Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
Exporting the Report. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
Step 4: Export Table Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
Exporting Individual Tables. . . . . . . . . . . . . . . . . . . . . . . . . . 165
Exporting Combined Tables . . . . . . . . . . . . . . . . . . . . . . . . . 166
Copying and Pasting Table Data . . . . . . . . . . . . . . . . . . . . . 167
Step 5: Print Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
Other Export Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168
Exporting from the Samples Plot . . . . . . . . . . . . . . . . . . . . . 168
Exporting from the GeneMapper ID-X Manager. . . . . . . . . . 168
Exporting from the Panel Manager . . . . . . . . . . . . . . . . . . . . 169
Exporting from the Profile Manager . . . . . . . . . . . . . . . . . . . 169
Index. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
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GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Preface
How to Use This Guide
Purpose of This
Guide
The GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
explains how to perform AmpFlSTR&reg; kit data analysis using the
GeneMapper&reg; ID-X Software Version 1.0. This guide functions as
both:
• A tutorial, using example experimental data provided with the
GeneMapper ID-X Software.
• A guide for your own experiments.
In addition, this guide introduces you to the features of the
GeneMapper&reg; ID-X Software Version 1.0.
Audience
Assumptions
This guide is written for forensic analysts who perform AmpFlSTR&reg;
kit data analysis using the GeneMapper ID-X Software.
This guide assumes that you have:
• Installed GeneMapper ID-X Software version 1.0 as described
in the GeneMapper&reg; ID-X Software Version 1.0 Installation
Guide.
• Used AmpFlSTR&reg; amplification kit data for human
identification (HID) applications.
• Developed a working knowledge of the Microsoft&reg; Windows&reg;
XP operating system.
Text Conventions
This guide uses the following conventions:
• Bold text indicates user action. For example:
Type 0, then press Enter for each of the remaining fields.
• Italic text indicates new or important words and is also used for
emphasis. For example:
Before analyzing, always prepare fresh matrix.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
ix
Preface
How to Use This Guide
• A right arrow symbol () separates successive commands you
select from a drop-down or shortcut menu. For example:
Select FileOpenSpot Set.
Right-click the sample row, then select View Filter
View All Runs.
User Attention
Words
Two user attention words appear in Applied Biosystems user
documentation. Each word implies a particular level of observation
or action as described below:
Note: – Provides information that may be of interest or help but is
not critical to the use of the product.
IMPORTANT! – Provides information that is necessary for proper
instrument or software operation, accurate chemistry kit use, or safe
use of a chemical.
Examples of the user attention words appear below:
Note: Each registered user has his or her own set of preferences.
When you set these options, if affects only the user currently logged
in.
IMPORTANT! To verify your client connection to the database, you
need a valid user ID and password.
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GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Preface
How to Obtain More Information
How to Obtain More Information
Related
Documentation
The following related documents are shipped with the system:
• GeneMapper&reg; ID-X Software Version 1.0 Installation Guide –
Provides procedures for installing version 1.0 of the
GeneMapper&reg; ID-X Software.
• GeneMapper&reg; ID-X Software Version 1.0 Administrator’s
Guide – Provides procedures for creating user accounts, user
groups, and security groups; configuring the audit trail and
E-signature tools; and maintaining version 1.0 of the
GeneMapper&reg; ID-X Software.
• GeneMapper&reg; ID-X Software Version 1.0 Help – Contains
context-sensitive help for all screens, and provides procedures
and background information needed to use the software.
• GeneMapper&reg; ID-X Software Version 1.0 Quick Reference
Guide – Provides abbreviated procedures for analyzing,
viewing, and interpreting data using GeneMapper&reg; ID-X
Software.
• GeneMapper&reg; ID-X Software Version 1.0 Reference Guide –
Describes peak detection, sizing, and genotyping algorithms,
and the GeneMapper&reg; ID-X Software quality value system.
Portable document format (PDF) versions of this guide and the other
documents listed above are also available on the GeneMapper&reg; ID-X
Software Version 1.0 Documentation CD.
Note: To open the user documentation included on the
GeneMapper&reg; ID-X Software Version 1.0 Documentation CD, use
the Adobe&reg; Acrobat&reg; Reader&reg; software available from
www.adobe.com.
Note: For additional documentation, see “How to Obtain Support”
on page xiii.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
xi
Preface
How to Obtain More Information
Obtaining
Information from
the Help System
The GeneMapper&reg; ID-X Software has a Help system that describes
how to use each feature of the user interface. Access the Help system
by doing one of the following:
• Click
in the toolbar of the Project window
• Select HelpContents and Index
• Press F1
You can use the Help system to find topics of interest by:
• Reviewing the table of contents
• Searching for a specific topic
• Searching an alphabetized index
You can also access PDF versions of all documents in the
GeneMapper&reg; ID-X Software document set from the Help system.
Send Us Your
Comments
Applied Biosystems welcomes your comments and suggestions for
improving its user documents. You can e-mail your comments to:
[email protected]
IMPORTANT! The e-mail address above is only for submitting
comments and suggestions relating to documentation. To order
documents, download PDF files, or for help with a technical
question, go to http://www.appliedbiosystems.com, then click the
link for Support. (See “How to Obtain Support” on page xiii).
xii
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Preface
How to Obtain Support
How to Obtain Support
For HID support, you can send an e-mail to
[email protected] or call 888-821-4443
option 1.
For HID support outside North America, contact your local support
office.
For the latest services and support information for all locations, go to
http://www.appliedbiosystems.com, then click the link for
Support.
At the Support page, you can:
• Access worldwide telephone and fax numbers to contact
Applied Biosystems Technical Support and Sales facilities
• Search through frequently asked questions (FAQs)
• Submit a question directly to Technical Support
• Order Applied Biosystems user documents, MSDSs,
certificates of analysis, and other related documents
• Download PDF documents
• Obtain information about customer training
• Download software updates and patches
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
xiii
Preface
How to Obtain Support
xiv
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 1
Getting Started
Chapter 1
Getting Started
This chapter covers:
■ Overview of the GeneMapper&reg; ID-X Software Version 1.0 . . 2
■ GeneMapper&reg; ID-X Software and Analysis Workflows . . . . . 6
■ The GeneMapper&reg; ID-X Software Quality Value System . . . . 7
Chapter 2
■ GeneMapper&reg; ID-X Software Security . . . . . . . . . . . . . . . . . 14
Setting Up the Software
■ GeneMapper&reg; ID-X Software Terms . . . . . . . . . . . . . . . . . . . 15
■ How to Use This Guide. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Chapter 3
Creating a Project,
Analyzing, and Reviewing
Analysis Workflow
Summaries
Chapter 4
Manually Reviewing and
Interpreting Data
Chapter 5
Performing Quality
Control of Sample
Results
Chapter 6
Performing
Peer/Technical Review of
Electronic Data
Chapter 7
Reporting, Exporting and
Printing Results
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
1
Chapter 1 Getting Started
Overview of the GeneMapper&reg; ID-X Software Version 1.0
Overview of the GeneMapper&reg; ID-X Software
Version 1.0
GeneMapper&reg; ID-X Software Version 1.0 is an automated
genotyping software solution for all human identification (HID) data
analysis needs, including forensic casework, databasing, and
paternity testing. The workflow for performing AmpFlSTR&reg; kit data
analysis with GeneMapper ID-X Software is shown below.
Process samples with AmpFlSTR&reg; kits
Run samples on instrument:
• ABI PRISM &reg; 310 Genetic Analyzer
• ABI PRISM &reg; 3100-Avant/3100 Genetic Analyzer
• Applied Biosystems 3130/3130xl Genetic Analyzer
Analyze samples in GeneMapper&reg; ID-X
Software:
• Size based on:
– Size standard run with chemistry
– Size standard specified in software
75 bp
450 bp
• Genotype based on:
– Allelic ladders run with chemistry
– Panels and bins specified in
software
Note: GeneMapper&reg; ID-X Software has undergone a verification
process defined by Applied Biosystems. However, human
identification laboratories analyzing forensic, paternity, databasing
and single-source samples that choose to use GeneMapper ID-X
Software for data analysis should perform their own appropriate
validation studies.
2
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 1 Getting Started
Features of the GeneMapper&reg; ID-X Software
Features of the GeneMapper&reg; ID-X Software
The software provides a quality value system and a set of streamlined
data review tools and features for both expert system and traditional
manual review workflows. Included in the system are the following
features:
Analysis
Requirement
Check
Allelic Ladder
Quality
Assessment
Analysis
Summary
Comprehensive
Quality Value
System
The analysis requirement check identifies unmet requirements
before analysis starts. For example, the software checks if there is a
sample with Sample Type = Allelic Ladder listed in the Samples
table. The system can be set up to stop analysis and display an alert if
this sample type is not found.
The allelic ladder quality assessment:
• Evaluates allelic ladders (based on system-defined allelic ladder
quality requirements) before proceeding to sample analysis
• Flags run folders without at least one passing allelic ladder. You
can review allelic ladders before proceeding with analysis.
• Automatically excludes low-quality ladders from analysis and
continues analysis with passing ladders. You can optionally
override the software assessment and use low-quality ladders to
generate bin offsets.
For efficient data evaluation, the analysis summary provides:
• An easy-to-view summary of analysis results
• An overview of allelic ladder, control, and sample quality
• A separation of passing samples from samples that do not meet
one or more quality thresholds
• Interactive links to specific categories of samples
(passing/check/low quality, allelic ladder/control/sample)
Note: For more information on the Quality Value system, see “The
GeneMapper&reg; ID-X Software Quality Value System” on page 7.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
3
Chapter 1 Getting Started
Features of the GeneMapper&reg; ID-X Software
Manual Review
Tools
For efficient data review in traditional manual review and expert
systems workflows, the manual review tools provide:
•
•
•
•
Process quality value (PQV) flags ( ,
,
)
Automatic spike labeling based on intelligent rules
User-defined “artifact” peak labels
Marker-specific quality value details with thresholds and
observed values displayed to show deviations from thresholds
and identify sources of anomalies
• Mark Sample for Deletion and Delete All Labels from Sample
functions in the Samples plot to allow easy elimination of
low-quality samples directly from the plot window
• Override Genotype Quality (GQ) and Composite Genotype
Quality (CGQ) functions to “manually accept” genotypes at the
marker and sample level
• Detailed label edit table display and visual indicators to indicate
edits (gray PQVs) for electronic peer/technical review
Quality Control
The quality control features:
• Evaluate sample concordance and allele matching
• Support additional custom positive controls and allow
automatic concordance checks of custom controls
• Compare samples in a project to one another to determine if
they contain profiles similar to neighboring samples
• Compare samples in a project to laboratory reference and
custom control profiles using a user-defined match percent
threshold
Chain-of-Custody
Systems for
Electronic Data
The chain-of-custody systems for electronic data can be
custom-configured (or turned off) by the GeneMapper ID-X System
administrator as needed. These systems provide:
• Security that controls user access to software functions and
data, and allows custom configuration that meets the datasharing needs of your laboratory and limits access to data when
needed
• Auditing that tracks changes and provides audit history reports
4
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 1 Getting Started
Features of the GeneMapper&reg; ID-X Software
• E-signature that requires user-authentication before changes are
saved
For more information on these features, see the GeneMapper&reg; ID-X
Software Version 1.0 Administrator’s Guide.
Multi-User
Database
Environment
Report Manager
The multi-user database environment:
• Allows multiple users to share projects in a centralized database
• Facilitates efficient data sharing between analysts for second
analysis and review
• Limits the need to import and export projects
• Allows central management of analysis settings
For customized table-formatted reports, the Report Manager:
• Allows you to change column names and column order
• Can export a traditional horizontal allele table for a selected
group of samples for use as a genotype summary or import into
LIMS or other downstream applications
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
5
Chapter 1 Getting Started
GeneMapper&reg; ID-X Software and Analysis Workflows
GeneMapper&reg; ID-X Software and Analysis
Workflows
The following flowchart summarizes the steps for performing a
typical data analysis workflow using the GeneMapper&reg; ID-X
Software. To the left are the steps the user performs when analyzing
samples and interpreting results. To the right are the software
operations that occur automatically during analysis.
Set up the software (one time):
1. (Optional) Create table and plot settings.
2. Create an analysis method.
3. Set Project Options.
Create a project:
1. Add samples.
2. Apply analysis settings.
During analysis, the software
does the following:
3. Start analysis.
Review analysis workflow summaries:
Analysis
requirements check
• (Optional) Analysis Requirements Summary
• (Optional) Allelic Ladder Analysis Summary
• Analysis Summary
Manually review required samples
(based on your lab protocol):
1. View sample-level quality flags.
Peak detection and
sizing
Allelic ladder quality
assessment
2. Display plots and view marker-level quality
flags and peak data.
3. (Optional) Edit allele labels.
Genotyping
4. (Optional) Manually accept genotypes.
(Optional) Use the Profile Comparison tool.
Sample quality
assessment
(Optional) Report results:
1. Generate a custom report.
Analysis summary
generation
2. Export reports and tables.
3. Print.
6
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 1 Getting Started
The GeneMapper&reg; ID-X Software Quality Value System
The GeneMapper&reg; ID-X Software Quality Value
System
Overview
The GeneMapper&reg; ID-X Software quality value system:
• Assesses the quality of allelic ladders before analysis and does
not consider low-quality allelic ladders for genotyping.
• Assesses the quality of data at the sample and marker level
using PQVs.
• Can be used in an optimized and validated expert system or
traditional manual review workflow to quickly identify data
quality issues and aid in interpretation of samples that do not
meet all thresholds.
• Can be used in an optimized and validated expert system
workflow to quickly segregate samples that require manual
review from those that do not.
The PQV results of the quality assessment are displayed as
color-coded flags: Pass ( ), Check, ( ), Low Quality (
). The
color of the flag depends on software-specified thresholds or userdefined thresholds set in the analysis method.
Optimizing and
Validating an
Expert System
Before using any software as an expert system, optimize and validate
the thresholds for each AmpFlSTR&reg; kit and instrument platform
combination by processing a variety of samples that challenge each
of the different quality flags.
IMPORTANT! Different kit/instrument combinations may require
different thresholds.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
7
Chapter 1 Getting Started
The GeneMapper&reg; ID-X Software Quality Value System
Quality Value System Checks and Assessments
The GeneMapper ID-X Software quality value system performs the
following checks and assessments:
• Analysis requirements checks – Before analysis starts,
identifies any conditions that may prevent analysis or cause
unexpected results.
• Sizing quality assessment – Evaluates the quality of the size
standard profile in each sample.
• Allelic ladder quality assessment – Evaluates allelic ladder
quality. Also determines if an allelic ladder is used for creating
bin offsets.
• Marker-level quality assessment – Evaluates labeled peaks
within each marker. Contributes to the overall genotype quality
assessment.
• Sample-level quality assessment – Evaluates the quality of the
entire sample.
• Genotype quality assessment – Evaluates the quality of each
marker in a sample. Contributes to the overall composite
genotype quality assessment.
The following sections contain a brief description of each quality
value system check and assessment along with a list of each
sample-level and marker-level quality value.
Note: For more information on the quality value system, see the
GeneMapper&reg; ID-X Software Version 1.0 Reference Guide.
8
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 1 Getting Started
The GeneMapper&reg; ID-X Software Quality Value System
Analysis Requirements Checks
The analysis requirements checks are performed and results
displayed either in the Samples table before analysis starts or in the
Analysis Requirements Summary after analysis starts.
Acronym
ARNM
Full Name
Analysis
Requirement
Not Met
Description and Flags
Indicates if all analysis requirements are met. These requirement
checks are performed when analysis is started:
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Sample File Not Found
Analysis Method Not Selected
Analysis Method Not Found in the Database
Panel Not Selected
Panel Not Found in the Database
Binset Not Selected
Binset in Analysis Method Does Not Match Binset Selected in the
Panel Manager
Size Standard Not Selected
Size Standard Not Found in Database
Size Standard Dye Color is Not Present in the Sample Dye Set
Matrix Not Selected
Matrix Not Found or Contains Invalid Data
No Allelic Ladder Selected in Run Folder
GMID v3.x Analysis Method Selected
Basic or Classic Size Standard Selected
SNP Panel Selected
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
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Chapter 1 Getting Started
The GeneMapper&reg; ID-X Software Quality Value System
Sizing Quality Assessment
The quality value system evaluates the quality of the size standard
profile within each sample (SQ) and allows you to flag size
standards with poor peak resolution. Sizing quality assessment is
displayed in the Samples table after analysis completes.
Acronym
SQ
Full Name
Sizing
Quality
Description and Flags
Evaluates the similarity between the fragment pattern for the size
standard dye specified in the size standard definition and the actual
distribution of size standard peaks in the sample, calculates an interim
SQ (a value between 0 and 1), then applies the broad peak weighting
specified in the analysis method, as described in the GeneMapper&reg; ID-X
Software Version 1.0 Reference Guide.
Note: The GeneMapper ID-X Software does not genotype samples with
SQ.
Allelic Ladder Quality Assessment
The quality value system performs an allelic ladder quality assessment
to determine if a ladder is used in genotyping (to create bin offsets).
Allelic ladder samples are analyzed before all other samples. An allelic
ladder sample must have a
SQ and a
CGQ to be used for
creating bin offsets. For an allelic ladder to have a
CGQ, all the
markers within the allelic ladder must pass the following rules:
Rule
Description
1
All ladder alleles specified in the panel used to analyze are detected.
2
In each marker, the peak height ratio of the first and second peak is greater than 50%.
This rule eliminates allelic ladders if the stutter peak before the first true allele peak is labeled as
an allele.
3
No spikes are detected above 20% (default) of the highest allele peak in the same dye color within
the extended marker range.
Note: Spike detection for allelic ladders is performed within each extended marker range (no
gaps are present between markers; the end point of each marker is extended past the marker
definition in the panel to the beginning of the next marker).
Note: The Allelic Ladder Spike Cut-off value is user-definable in the Peak Quality tab of the
analysis method.
4
10
The peak height ratio between the lowest and highest peak is equal to or greater than 15%.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 1 Getting Started
The GeneMapper&reg; ID-X Software Quality Value System
Marker-Level Quality Assessments
Marker-level quality assessments indicate the quality of each marker
in a sample and are displayed in the Genotypes table after analysis
completes.
Acronym
Full Name
Description and Flags
OS
Off-scale
Indicates if any fluorescence signal within the marker exceeds the
detection threshold of the instrument.
BIN
Out of Bin
Allele
Indicates if labeled peaks do not fall inside bins. These peaks are
labeled with OL (Off ladder).
PHR
Peak Height
Ratio
Indicates if the peak height ratio between the lowest and highest peak
is less than the Min Peak Height Ratio defined in the analysis method.
MPH
Max Peak
Height
Indicates if any peak heights (in RFU) within the marker size range
exceed the Max Peak Height value (in RFU) set in the analysis method.
LPH
Low Peak
Height
Indicates if any peak heights (in RFU) within the marker size range are
below the following thresholds set in the analysis method:
• Homozygous Min Peak Height
• Heterozygous Min Peak Height
AN
Allele Number
Indicates if the software detects no alleles, more than the Max
Expected Alleles set in the analysis method (Peak Quality tab), or no X
allele detected in amelogenin.
BD
Broad Peak
Indicates if the width of any peak exceeds the Max Peak Width (half
height in base pairs) defined in the analysis method (Peak Quality tab).
CC
Control
Concordance
Indicates if a positive, custom, or negative control produces the
expected profile.
SPK
Marker Spike
• Allelic ladders – Indicates if spikes are detected within each extended
marker range (no gaps are present between markers; the end point of
each marker is extended past the marker definition in the panel to the
beginning of the next marker).
• Samples – Indicates if spikes are detected within a marker size range.
The software uses a proprietary algorithm that detects spikes based on the
peak morphology.
OVL
Overlapping
Alleles
Indicates if a labeled peak (allele or artifact) falls within the size ranges of
two neighboring markers.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
11
Chapter 1 Getting Started
The GeneMapper&reg; ID-X Software Quality Value System
Genotype Quality Assessment
For samples, the quality value system assigns the GQ for each
marker based on the individual marker quality flags. For allelic
ladders, the quality value system assigns a GQ for each marker based
on the allelic ladder quality requirements, as described in “Allelic
Ladder Quality Assessment” on page 10. The GQ is used to
determine the CGQ, and is displayed in the Genotypes table after
analysis completes.
Acronym
Full
Name
GQ
(samples)
Genotype
Quality
Description and Flags
Indicates the genotype quality of the marker in the sample. The genotype
quality for a sample marker is determined based on the presence of labeled
peaks detected (after filtering) and the GQ weighting specified in the
analysis method.
If no labeled peaks are detected (and the sample is not a negative control),
the GQ is set to 0. If one or more labeled peaks are detected, the GQ is
initially set to 1 with a final value determined by the GQ weighting of
individual marker-level quality values as specified in the analysis method.
GQ
(allelic
ladders)
Genotype
Quality
Indicates the genotype quality of the marker in the allelic ladder. The
genotype quality for an allelic ladder marker is determined using systemdefined quality rules (as described in the GeneMapper&reg; ID-X Software
Version 1.0 Reference Guide) to ensure:
• All expected peaks are present.
• Peak height ratio of the first and second peak is greater than 50%.
• No spikes are present in the extended marker range (within or between
markers).
• The peak height ratio between the lowest and highest peak is equal to or
greater than 15%.
IMPORTANT! If the Allelic Ladder GQ Weighting for Spikes is set to 0 (off)
in the analysis method, the GQ may be
allelic ladder.
12
, even if spikes are present in the
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 1 Getting Started
The GeneMapper&reg; ID-X Software Quality Value System
Sample-Level Quality Assessments
Sample-level quality assessments that indicate the quality of the
entire sample are displayed in the Samples table after analysis
completes.
Acronym
Full Name
Description and Flags
SOS
Sample
Off-scale
Indicates if any fluorescence signal within the analysis range exceeds
the detection threshold of the instrument.
MIX
Mixed Source
Indicates a potential mixed-source sample.
OMR
Outside
Marker Range
Indicates if labeled peaks are detected between two marker size
ranges defined in the panel.
SSPK
Sample Spike
• Allelic ladders – Indicates if spikes are detected within the sizing
range.
• Samples – Indicates if spikes are detected within or between two
defined marker size ranges. Does not indicate if spikes are detected
before the first marker or after the last marker.
The software uses a proprietary algorithm that detects spikes based on
the peak morphology.
CGQ
(samples)
Composite
Genotype
Quality
Indicates overall sample genotype quality. Considers the individual
marker GQ values.
CGQ
(allelic
ladders)
Composite
Genotype
Quality
Indicates overall allelic ladder quality. Considers the allelic ladder
quality assessment (see page 10).
Note: Allelic ladder samples with
CGQ are not used to create bin
offsets.
IMPORTANT! If the Allelic Ladder GQ Weighting for Spikes is set to 0
(off) in the analysis method, the CGQ may be
even if spikes are
present in the allelic ladder.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
13
Chapter 1 Getting Started
GeneMapper&reg; ID-X Software Security
GeneMapper&reg; ID-X Software Security
The GeneMapper&reg; ID-X Software contains a security system that
includes the following features relevant to the procedures outlined in
this guide:
Security System
Component
User accounts
Description
A required component of the security system that allows only authorized users
to access the software.
This guide assumes that you log in using the Practice User account provided
with the software (see the GeneMapper&reg; ID-X Software Version 1.0
Administrator’s Guide for a description of user accounts). Chapter 2 provides
detailed instructions for logging in.
Security groups
A component of the security system that restricts user access to specific data
items (project, panels, analysis methods, and size standards.)
When using the Practice User account,
data is assigned to the Practice Security
Group automatically (you are not prompted
to select a security group).
Audit trail
A component of the security system that
keeps track of changes made and can
require users to provide a reason for a
change.
The audit trail is set up by default to require
a reason for change when you edit allele
labels. If additional auditing is set up on
your system, you may be prompted to
specify a reason when you create or edit
data items.
E-signature
An optional component of the security
system that requires users to provide a
valid user name and password when they
make a change.
This guide assumes that E-signature is
not set up on your system.
If E-signature is set up on your system,
you are prompted to provide your user
name and password when you create or
edit data items.
14
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 1 Getting Started
GeneMapper&reg; ID-X Software Terms
For information on:
• Setting up security, audit trail, and E-signature on your system,
see the GeneMapper&reg; ID-X Software Version 1.0
Administrator’s Guide.
• Using security groups (and the impact that security groups have
on the data you can access), using the audit trail, and using
E-signature, see the GeneMapper&reg; ID-X Software Help.
GeneMapper&reg; ID-X Software Terms
Some common terms used in this guide are:
Term
Definition
allele
Variant form of a marker (locus).
allelic ladder
A sample that contains a set of alleles that are representative of those found in a
particular STR marker. Allelic ladders are generated with the same primers as tested
samples, providing a reference DNA size for each allele included in the ladder.
Unknown samples are compared against them to determine their genotype.
AmpFlSTR&reg;
Chemistry kit
Applied Biosystems Human Identification PCR amplification kits for short tandem
repeat (STR) analysis.
analysis
method
A collection of user-defined settings that determine the sizing, genotyping and
quality value algorithms used by the GeneMapper&reg; ID-X Software to analyze sample
files in a project.
bin
A fragment size (&plusmn; 0.5 bp) that defines an allele within a marker.
bin set
A collection of bins (allele definitions), typically specific to a set of panels.
CODIS
The FBI Laboratory Combined DNA Index System. For more information, see:
http://www.fbi.gov/hq/lab/codis/index1.htm
custom
control
A positive amplification control other than the control DNA supplied with the
AmpFlSTR&reg; kits.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
15
Chapter 1 Getting Started
GeneMapper&reg; ID-X Software Terms
Term
expert system
Definition
A computer program that:
•
•
•
•
•
•
•
•
Interprets alleles and DNA profiles
Uses knowledge acquired from Qualified Analysts
Is Rule-based
Acts as an “assistant” to Qualified Analysts
Automated–minimal human intervention
Is as good or better than human experts
Documents reasoning behind decisions
Does not require manual review of “passing” samples
Source: National DNA Index System (NDIS) DNA Data Acceptable Standards,
Appendix B, &quot;Guidelines for Submitting Requests for Approval of an Expert System
for Review of Offender Samples,&quot; 15 July 2004.
genotype
Allele designations for a genetic locus.
genotyping
Labeling of alleles based on allelic ladder bin comparisons and filtering of alleles
based on analysis method settings.
lab reference
profile
A genotyped profile of an analyst or other lab personnel.
marker
A genetic locus. A name, fragment size range in base pairs, dye color, repeat length,
and physical allelic ladder alleles are defined for each marker.
negative
control
A sample expected to generate no allele calls. Can be an extraction blank, reagent
blank or an amplification negative control.
panel
A group of markers and properties (size ranges, dye label color, expected positive
control genotypes). Each panel provided with the GeneMapper&reg; ID-X Software
represents a specific AmpFlSTR&reg; Chemistry kit.
positive
control
A sample of known genotype. Each AmpFlSTR&reg; Chemistry kit includes a positive
control. You can also run custom positive controls.
PQV (Process
Quality Value)
Process quality values (PQVs) assess the quality of data at the sample and marker
levels.
profile
The genotype (allele designations) of a sample.
project
In the GeneMapper&reg; ID-X Software, a collection of sizing and genotyping results for
a set of data.
run
The electrophoretic injection of a set of samples from a single plate (48- or 96-well)
and the resulting sample files.
run folder
A folder containing a set of sample files from a capillary-electrophoresis run.
16
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 1 Getting Started
How to Use This Guide
Term
Definition
sample files
Capillary-electrophoresis data files (*.fsa) generated by Data Collection Software.
size standard
definition
A list of fragment sizes in base pairs that a size standard sample contains. Only
those sizes required for accurate sizing are contained in the size standard definition.
stutter ratio
Percent value used to filter stutter peaks (remove labels).
traditional
manual review
Visual inspection of samples regardless of quality.
For additional definitions, see the GeneMapper&reg; ID-X Software Help
(select Glossary in the Contents tab).
How to Use This Guide
Before You Start
IMPORTANT! Before using the procedures in this guide, make sure
the GeneMapper&reg; ID-X Software has been successfully installed and
registered. See the GeneMapper&reg; ID-X Software Version 1.0
Installation Guide for more information.
When performing the procedures described in this guide, keep in
mind the following:
• The steps in each chapter are designed to flow from start to
finish, and from one chapter to the next
• Complete each chapter as a single unit before stopping your
work, if possible
• Make sure you perform each step as it is described
• Carefully review any previously performed steps if you observe
any differences between what is shown in this guide and what is
displayed on your own system
User Account
Requirements
You must use the Practice User account provided to perform the
procedures in this guide.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
17
Chapter 1 Getting Started
How to Use This Guide
Using the Guide
with the Example
Data Provided
Example data (.fsa) generated using the Applied Biosystems
AmpFlSTR&reg; Identifiler&reg; PCR amplification kit, and a reference
project (.ser) containing analyzed lab reference samples, custom
controls, and QC samples are installed with the GeneMapper&reg; ID-X
Software.
To perform the exercises described in this guide, use the example
files (.fsa and .ser) located on your computer as shown below.
File Location
Install
Configuration
Client install
Full install
Reference project (.ser)
Sample files (.fsa)
&lt;drive&gt;:\AppliedBiosystems\
GeneMapperID-X\Client\Example Data\
Projects
&lt;drive&gt;:\AppliedBiosystems\
GeneMapperID-X\Client\Example Data\
Identifiler Samples
&lt;drive&gt;:\AppliedBiosystems\
GeneMapperID-X\Example Data\
Projects
&lt;drive&gt;:\AppliedBiosystems\
GeneMapperID-X\Example Data\
Identifiler Samples
Note: The drive will vary depending on the installation of the
GeneMapper&reg; ID-X Software. The default installation drive is the
Local Disk drive. See the GeneMapper&reg; ID-X Software Version 1.0
Installation Guide for more information on installation options.
Using the Guide
as a Tutorial
This guide is a tutorial designed to help you follow a typical analysis
workflow. Using the example data provided with the GeneMapper
ID-X Software, follow the procedures in Chapters 2-7:
Chapter
Chapter 2, Setting Up the Software
Description
1. View default panels and bins
2. Create an analysis method
3. View default table and plot settings
4. Create new table and plot settings
5. View default size standard definitions
6. Add custom control and lab reference profiles to database
7. Set project options
18
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 1 Getting Started
How to Use This Guide
Chapter
Description
Chapter 3, Creating a Project,
Analyzing, and Reviewing Analysis
Workflow Summaries
1. Create a project and add samples
2. Analyze the data
3. Review the Analysis Requirement Summary
4. Review the Analysis Summary
Chapter 4, Manually Reviewing and
Interpreting Data
1. View electropherograms
2. Interpret anomalies using quality value flags and details
3. Edit allele labels
4. Manually accept marker genotypes
Chapter 5, Performing Quality
Control of Sample Results
1. Perform Sample Concordance check
2. Perform Sample Comparison check
3. Perform Lab Reference Comparison check
4. Perform Control/QC Sample Comparison check
Chapter 6, Performing
Peer/Technical Review of Electronic
Data
1. Use filtered tables to find edited samples
2. Use Label Edit Viewer to view edited labels
3. Manually accept sample profiles
4. View edit comments in tables
Chapter 7, Reporting, Exporting and
Printing Results
For More
Information
1. Generate a custom report
2. Export reports and tables
This guide contains basic procedures. It does not describe all features
and parameters in the GeneMapper&reg; ID-X Software. For detailed
information on topics presented in this guide, see the GeneMapper&reg;
ID-X Software Help.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
19
Chapter 1 Getting Started
How to Use This Guide
20
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 2
Setting Up the Software
This chapter covers:
Chapter 1
Getting Started
■ Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
■ Step 1: Start the Software and Log In. . . . . . . . . . . . . . . . . . . 22
■ Step 2: View Panels, Bins, and Stutter Settings . . . . . . . . . . . 26
Chapter 2
Setting Up the Software
■ Step 3: Create an Analysis Method. . . . . . . . . . . . . . . . . . . . . 29
■ Step 4: Review Default Table Settings, Plot Settings, and Size
Standards. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
■ Step 5: Import Lab Reference and Custom Control Profiles . 47
Chapter 3
Creating a Project,
Analyzing, and Reviewing
Analysis Workflow
Summaries
■ Step 6: Set the Project Options . . . . . . . . . . . . . . . . . . . . . . . . 52
Chapter 4
Manually Reviewing and
Interpreting Data
Chapter 5
Performing Quality
Control of Sample
Results
Chapter 6
Performing
Peer/Technical Review of
Electronic Data
Chapter 7
Reporting, Exporting and
Printing Results
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
21
Chapter 2 Setting Up the Software
Overview
Overview
This chapter demonstrates how to prepare the GeneMapper&reg; ID-X
Software for analysis, using the example data set provided with the
software.
In This Chapter
In this chapter you will learn how to:
•
•
•
•
Start the software and log in
Review the panels, bins, and stutter files provided
Create analysis methods
Review the table settings, plot settings and size standards
provided
• Create new table settings and plot settings
• Import lab reference and custom control profiles
• Set project options
Step 1: Start the Software and Log In
Starting the
Software and
Logging In
22
1. Double-click
(GeneMapper&reg; ID-X v1.0) on the desktop to
launch the software.
2. In the Login to GeneMapper&reg; ID-X dialog box, enter Practice
User for User Name and password for Password, then click
OK.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 2 Setting Up the Software
Step 1: Start the Software and Log In
Note: If you have logged in before, you can select the user
name from the drop-down list.
The Project window opens.
Toolbar
Menu
Project name
Logged in user
Navigation pane that lists run
folders (blank for new projects)
Computer name
Content pane showing Samples
table (blank for new projects)
Status bar
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
23
Chapter 2 Setting Up the Software
Step 1: Start the Software and Log In
Resizing and
Exploring the
Project Window
1. Adjust the window to display as many of the table columns as
possible:
a. Click
(Maximize) in the upper right corner of the
Project window to expand the window to occupy the full
area of the screen.
b. Resize columns by dragging the separating lines:
• Position the pointer over the line separating two
columns until the pointer changes to sizing arrows.
• Click-drag the sizing arrows. Dragging to the left
narrows the left-hand column. Dragging to the right
widens the left-hand column.
2. Place the pointer over toolbar buttons to display tooltips that
explain the function of the button.
Exploring the
Context-Sensitive
Help System
The GeneMapper&reg; ID-X Software context-sensitive Help system
provides immediate access to detailed information regarding
software views, functions and troubleshooting guidelines.
To access the Help system from the Project window:
1. Click the Help menu, then select Contents and Index.
24
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 2 Setting Up the Software
Step 1: Start the Software and Log In
Help opens in a separate window.
Note: You can also access the Help system anywhere in the
software by pressing F1, by clicking
in the toolbar of the
Project window, or by clicking the Help button in a window, tab
or dialog box to access help topics specific to that particular
feature of the user interface. You can then click on the internal
links within the specific help topic to navigate to related topics.
2. Click
(Close) to close the Help window and return to the
Project window.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
25
Chapter 2 Setting Up the Software
Step 2: View Panels, Bins, and Stutter Settings
Step 2: View Panels, Bins, and Stutter Settings
Overview
Before analyzing data, the software must have access to
AmpFlSTR&reg; kit details such as marker size ranges and dyes, allele
sizes, and stutter ratios. The files that contain this information are
called Panel, Bin, and Stutter files, respectively.
IMPORTANT! The panel, bin and stutter values shown in this section
are configured specifically for use with AmpFlSTR&reg; kit data.
Applied Biosystems recommends you use the provided panels and
bins when analyzing AmpFlSTR&reg; data from your laboratory, unless
your laboratory has validated alternative values.
When to Import
As part of the GeneMapper&reg; ID-X Software installation process, the
panel, bin and stutter files are automatically imported into the
GeneMapper&reg; ID-X Software database.
Note: If you have installed GeneMapper&reg; ID-X Software on the
same workstation as Data Collection software (co-installation), you
must manually import the panel and bin files. See the GeneMapper&reg;
ID-X Software Help for information on this procedure.
Note: You can import new panel, bin and stutter files whenever
updated versions are provided.
Viewing Panel,
Bin, and Stutter
Settings
26
1. If not already started, launch the GeneMapper&reg; ID-X Software
(see page 22).
2. In the Project window toolbar, click
(Panel Manager).
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 2 Setting Up the Software
Step 2: View Panels, Bins, and Stutter Settings
3. In the navigation pane of the Panel Manager, select the
AmpFLSTR_Panels_v1X kit folder, then click
to expand
its contents.
4. Double-click the Identifiler_v1X panel folder. The markers
found in the Identifiler kit are listed in the navigation pane and
the marker details are displayed in the content pane.
Markers
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Marker details
27
Chapter 2 Setting Up the Software
Step 2: View Panels, Bins, and Stutter Settings
5. Double-click the D8S1179 marker in the navigation pane. A
plot showing the bins for this marker is displayed in the content
pane.
Markers can include two bin types: physical (represent alleles
present in the allelic ladder sample) and virtual (represent
alleles not present in the allelic ladder sample). The software
displays all physical bins in grey, and all virtual bins (except for
CODIS bins) in pink. In this example, the D8S1179 marker
contains two virtual bins, 7 and 20, displayed in pink in the
content pane.
6. In the navigation pane, click
folder.
to expand the Yfiler_v1X panel
7. Click
to expand the Y_DYS392 marker, then select Stutter
Ratio &amp; Distance.
28
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 2 Setting Up the Software
Step 3: Create an Analysis Method
The marker-specific stutter ratios defined in the stutter file are
displayed in the content pane. In this example, both Minus and
Plus stutter ratios are specified for this marker.
Note: From this window, you can apply up to four minus and
four plus stutter ratios per marker, and edit the default stutter
percentages provided with the GeneMapper&reg; ID-X Software.
8. Click OK to close the Panel Manager window.
Step 3: Create an Analysis Method
Overview
In This Section
Analysis methods define the peak detection, sizing, genotyping, and
quality assessment parameters applied during analysis of sample
data.
In this section, you will create a new analysis method, configured
specifically for use with the example data provided with the
GeneMapper&reg; ID-X Software, and with the procedures outlined in
this guide.
IMPORTANT! The values used in this guide may not be suitable for
analyzing data generated in your laboratory. You must optimize and
validate these values during internal verification.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
29
Chapter 2 Setting Up the Software
Step 3: Create an Analysis Method
Creating the
Analysis Method
1. In the Project window toolbar, click
Manager).
(GeneMapper ID-X
2. Select the Analysis Methods tab, then click New.
3. Complete the tabs of the Analysis Method Editor for this
example analysis method as described in Table 1 on page 30,
and use the GeneMapper&reg; ID-X Software Help to learn more
about the purpose of specific settings and the effects of
changing these settings as needed.
Table 1
Analysis method settings for the example data (Identifiler&reg; samples)
Tab
General
Settings
Enter the settings as shown below:
Note: When following the procedures in this guide, Applied Biosystems recommends
you add your initials to the names of data objects you create so you can distinguish
your data objects from similar objects that may be saved to the same GeneMapper&reg;
ID-X Software database by other laboratory personnel when performing the same steps
in this guide.
Note: This analysis method is assigned to the Practice Security Group automatically
(you are not prompted to select a security group), and is only available if you log in to
the software with the Practice User account. You will verify the Project Options set for
the Practice User account in “Step 6: Set the Project Options” on page 52.
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GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 2 Setting Up the Software
Step 3: Create an Analysis Method
Table 1
Tab
Allele
Analysis method settings for the example data (Identifiler&reg; samples) (continued)
Settings
Select the bin set and review the default settings as shown below:
Note: This analysis method specifies marker-specific stutter ratios. In this case, the
stutter ratios viewed in the Panel Manager will be applied. However, a Global Cut-off
Value and a Global Minus Stutter Ratio may be applied for single-source samples to
minimize background labeling that could cause samples to be flagged as low quality.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
31
Chapter 2 Setting Up the Software
Step 3: Create an Analysis Method
Table 1
Analysis method settings for the example data (Identifiler&reg; samples) (continued)
Tab
Peak
Detector
32
Settings
Enter the settings as shown below:
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 2 Setting Up the Software
Step 3: Create an Analysis Method
Table 1
Analysis method settings for the example data (Identifiler&reg; samples) (continued)
Tab
Settings
Peak
Quality
If a marker does not meet a PQV threshold value set in this tab, the GeneMapper&reg; ID-X
Software will set the marker PQV flag to yellow
(Check).
Review the default PQV threshold settings shown below. Click Help at the bottom of the
tab and navigate to the Peak Quality help topic to learn more about the parameters
presented in this tab.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
33
Chapter 2 Setting Up the Software
Step 3: Create an Analysis Method
Table 1
Analysis method settings for the example data (Identifiler&reg; samples) (continued)
Tab
SQ &amp; GQ
Settings
Settings
The values entered in this tab affect the calculation of SQ and GQ.
Review the default SQ and GQ settings shown below. Click Help at the bottom of the
tab and navigate to the SQ &amp; GQ Settings Tab help topic to learn more about the
parameters presented in this tab.
4. After completing all tabs, click Save to save your changes and
close the Analysis Method Editor dialog. The GeneMapper
ID-X Manager remains open.
34
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 2 Setting Up the Software
Step 4: Review Default Table Settings, Plot Settings, and Size Standards
Step 4: Review Default Table Settings, Plot
Settings, and Size Standards
Overview
In this section, you will review the default table, plot, and size
standard settings provided with the GeneMapper&reg; ID-X Software.
The default settings are designed to support a logical and efficient
data analysis and review workflow using the example data provided
with the software and for use when analyzing data generated in your
laboratory. Use of the default settings is demonstrated throughout
this guide.
Note: You can modify the default table, plot, and size standard
settings or create new settings to support individual laboratory
workflows.
Review Default Table Settings
Overview
Table settings determine the content (columns) displayed in or
exported from the Samples and Genotypes tables. The default table
settings shown in this section include specific columns required to
perform different workflow tasks.
Reviewing Table
Settings
1. Open the GeneMapper ID-X Manager if not already open (see
page 30).
2. In the GeneMapper ID-X Manager, select the Table Settings
tab.
3. Click a table row to select the table setting to review, then click
Open.
4. Review the default table settings provided using Table 2 on
page 36.
5. After you have finished reviewing the default table settings,
click OK to close the Table Settings Editor. The GeneMapper
ID-X Manager remains open.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
35
Chapter 2 Setting Up the Software
Step 4: Review Default Table Settings, Plot Settings, and Size Standards
Defaults Provided
Table 2
The following table settings are installed with the GeneMapper&reg;
ID-X Software.
Default table settings
Table Setting
Name
Column Settings
Purpose
Samples Table
310 Data
Analysis
Used to set up table data
to analyze sample files
generated on an
ABI PRISM &reg; 310 Genetic
Analyzer.
Displays analysis setting
columns and sample-level
quality values.
Displays marker and
allele columns, and
marker-level quality
values.
31XX Data
Analysis
Used to set up table data
to analyze sample files
generated on ABI PRISM &reg;
3100 Series and
Applied Biosystems 3130
Series Genetic Analyzers.
Same as 310 Data
Analysis table setting (see
entry above), except the
Matrix column is not
displayed.
Same as 310 Data
Analysis table setting
(see entry above).
CODIS Export
Used to enter data in the
appropriate columns of
the Samples table for
exporting a CODISsupported CMF file.
Displays the columns that
may be used to populate
CODIS-compatible fields
when the table is
exported in CMF file
format.
Same as 310 Data
Analysis table setting
(see entry above).
Used to import lab
reference and custom
control profiles into the
GeneMapper&reg; ID-X
Software database.
Displays the Profile ID
column, which is required
to name and enter profiles
into the GeneMapper&reg;
ID-X Software database.
Same as 310 Data
Analysis table setting
(see entry above).
View CGQ
Overrides
Used to quickly identify
samples that have been
manually accepted (this
includes samples with
and without allele edits).
Displays only samples
with CGQ override flag
and sample-level quality
values.
Displays marker and
allele columns, edit
comments and markerlevel quality values.
View Edited
Samples
Used to quickly identify
samples that have one or
more allele edit.
Displays only samples
with allele edits and
sample-level quality
values.
Displays only markers
with edits, edit
comments and markerlevel quality values.
Import
Reference
Profiles
36
Genotypes Table
Note: No action is
required on the
Genotypes tab when
exporting a CMF file.
Note: No action is
required on the
Genotypes tab when
importing reference
profiles.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 2 Setting Up the Software
Step 4: Review Default Table Settings, Plot Settings, and Size Standards
Table 2
Default table settings (continued)
Table Setting
Name
Traditional Allele
Table
Purpose
Used to export data into
an allele table using
Combined Table Export.
Column Settings
Samples Table
Genotypes Table
Displays only the sample
information required for
an allele table export
format.
Displays only the
marker and allele
information required for
an allele table export
format.
Note: The allele table export format
resembles that created in ABI PRISM &reg;
Genotyper&reg; Software. The table is
compatible with spreadsheet software
such as Microsoft&reg; Excel&reg;.
View Unedited
Samples
Used to quickly identify
samples that have not
been manually
manipulated (edited or
overridden).
Displays only samples
without label edits, or GQ
or CGQ override flags and
sample-level quality
values.
Displays only markers
without allele edits and
marker-level quality
values.
Yfiler Haplotype
DB Export
Used to export the
appropriate columns
using Combined Table
Export for upload into the
Yfiler&reg; Haplotype
Database.
Displays only the sample
information required for
export in Yfiler&reg;
Haplotype Database
format.
Displays only the
sample and marker
information required for
export in Yfiler&reg;
Haplotype Database
format.
VALID_GMIDX_
TableSetting-1.0
Used to export the
appropriate columns for
importing tabular data
into VALID™ Software.
Displays only the sample
information and run
information required for a
VALID softwarecompatible format.
Displays only the
marker information
required for a VALID
software-compatible
format.
Note: The columns in the Genotypes table displayed at the bottom of
the Samples plot are determined by the table setting selected in the
Project window.
Creating a New
Table Setting
With custom table settings, you can adjust your view of the Samples
and Genotypes tables to show or hide specific columns, and apply
filters to display only specific samples.
1. Open the GeneMapper ID-X Manager if not already open (see
page 30).
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
37
Chapter 2 Setting Up the Software
Step 4: Review Default Table Settings, Plot Settings, and Size Standards
2. In the GeneMapper ID-X Manager, select the Table Settings
tab, then click New to open the Table Setting Editor.
3. Enter the following information in the General tab:
4. Select the Samples tab, then expand the window (click-drag the
window border) to display the Column, Filtering and Content
columns in the Column Settings list:
Click-drag
border to
resize
window
5. Click Hide All to deselect all of the default table column
selections in the Column Settings list.
6. Select to Show ( ) the individual Samples table columns you
wish to display using this custom table setting.
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GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 2 Setting Up the Software
Step 4: Review Default Table Settings, Plot Settings, and Size Standards
7. Click the Filtering field for the Sample Type row, then select
Sample from the drop-down list.
Note: When you view the Samples table using this table setting,
the Samples table displays only sample files of sample type
Sample, and not Allelic Ladder or Control sample types. You
can then export this filtered view of the Samples table (as
described in Chapter 7).
8. Select additional filters to apply to the remaining columns in the
Samples table, if desired.
9. In the Sort by drop-down list, select Run Date &amp; Time.
Note: Each sample file records the run date and time for that
individual sample. When you view the Samples table using this
table setting, the sample files sort by order of injection rather
than the default sort option of by Sample File.
10. Select the Genotypes tab, then follow the same procedures
outlined in steps 5 through 8 above to select the columns to
display and filter in the Genotypes table.
Note: The settings you specify in the Genotypes tab determine
the columns displayed in the Genotypes table in the Project
window, and the Genotypes table in the Samples plot.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
39
Chapter 2 Setting Up the Software
Step 4: Review Default Table Settings, Plot Settings, and Size Standards
11. Verify the default sort options for the Genotypes table.
Note: The GeneMapper&reg; ID-X Software executes the selected
sort options in succession. By default, markers are sorted within
a sample by dye color (B, G, Y, R), then by size.
12. Click OK to apply your changes and close the Table Setting
Editor. The GeneMapper ID-X Manager remains open.
Review Default Plot Settings
Overview
Reviewing Plot
Settings
Plot settings determine the number of panes, headers, labels and
tables displayed in the Samples and Genotypes plot windows. The
default plot settings shown in this section include a specific set of
display elements required to perform different analysis workflow
tasks. These elements are designed for efficient data review.
1. Open the GeneMapper ID-X Manager if not already open (see
page 30).
2. In the GeneMapper ID-X Manager, select the Plot Settings tab.
3. Click on a table row to select the plot setting you wish to review,
then click Open.
4. Review the default plot settings provided using Table 3 on
page 41.
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GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 2 Setting Up the Software
Step 4: Review Default Table Settings, Plot Settings, and Size Standards
5. Click OK to close the Plot Settings Editor after reviewing all
plot settings. The GeneMapper ID-X Manager will remain open.
Defaults Provided
Table 3
The following plot settings are installed with the GeneMapper&reg; ID-X
Software.
Default plot settings
Plot Setting
Name
Purpose
Display Settings
Check LIZ
Size Standard
Used to display the GeneScan™ LIZ&reg;
size standard in the same format as
the Check GS500 Macro in the
ABI PRISM &reg; Genotyper&reg; Software
templates.
Displays the GeneScan™ LIZ&reg; size
standard fragments with labels per sample
in separate electropherogram panes.
Check ROX
Size Standard
Used to display the GeneScan™
ROX™ size standard in the same
format as the Check GS500 Macro in
the ABI PRISM &reg; Genotyper&reg; Software
templates.
Displays the GeneScan™ ROX™ size
standard fragments with labels per sample
in separate electropherogram panes.
Data
Interpretation
Used during manual review of sample
data, to enable quick interpretation of
anomalies and marker-level quality
values.
Displays the electropherogram plots for
the selected sample(s), the Genotypes
table, and the Quality Value Details (QVD)
pane.
Overlay LIZ
Dye
Used to perform sizing precision
checks with the GeneScan™ LIZ&reg;
size standards.
Overlays all selected size standard
fragments in one electropherogram pane,
and displays the Sizing table.
Overlay ROX
Dye
Used to perform sizing precision
checks with the GeneScan™ ROX™
size standards.
Overlays all selected size standard
fragments within a project in one
electropherogram pane, and displays the
Sizing table.
Sizing Data
Used to display data in a format
similar to the ABI PRISM &reg; GeneScan™
Software plots.
Displays all dyes per sample in one
electropherogram pane, and the Sizing
table.
Traditional
Genotype Plot
Used to display data in a format
similar to the ABI PRISM &reg; Genotyper&reg;
Software plots.
Displays each dye for a sample in a
separate electropherogram pane.
View Label
Edits
Used to display allele edits for the
selected sample(s) in a table below
the electropherogram for electronic
data review.
Displays the electropherogram plots for
the selected sample(s), and the Label Edit
Viewer table.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
41
Chapter 2 Setting Up the Software
Step 4: Review Default Table Settings, Plot Settings, and Size Standards
Creating a New
Plot Setting
Custom plot settings save frequently used combinations of display
elements to minimize the time spent adjusting display settings during
manual review.
1. Open the GeneMapper ID-X Manager if not already open (see
page 30).
2. In the GeneMapper ID-X Manager, select the Plot Settings tab,
then click New.
3. Enter the following information in the General tab of the Plot
Setting Editor:
4. Select the Sample Header tab, then select the columns to
display in the Samples plot header.
5. Select the Genotype Header tab, then select the columns to
display in the Genotypes plot header.
Note: The columns in the Genotypes table displayed at the
bottom of the Samples plot are determined by the table settings
selected in the Project window.
6. Select the Sizing Table tab, then select the columns to display
and the font and font size to use for the Sizing table displayed at
the bottom of the Samples plot.
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GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 2 Setting Up the Software
Step 4: Review Default Table Settings, Plot Settings, and Size Standards
7. Select the Labels tab, then select the label information to
display for the detected peaks in the Samples and Genotypes
plots:
Specify multiple
labels per category
This tab allows you to choose a different set of labels for
different types of samples and different types of peak labels. For
instance, you may choose to only display the allele call for all
allelic ladder samples, but you want to display both the allele
call and height on all other sample types and have them both be
displayed in the same plot window. Each peak can have up to
four labels.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
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Chapter 2 Setting Up the Software
Step 4: Review Default Table Settings, Plot Settings, and Size Standards
8. Select the Display Settings tab, then specify settings:
Select a checkbox or
radial button to enable the
associated toolbar button
Set the x-axis zoom range
Click Help at the bottom of the tab and navigate to the Display
Settings Tab help topic to learn more about the parameters
presented in this tab.
9. Click OK to apply your changes and close the Plot Setting
Editor. The GeneMapper ID-X Manager remains open.
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GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 2 Setting Up the Software
Step 4: Review Default Table Settings, Plot Settings, and Size Standards
Review Default Size Standards
Overview
Reviewing Size
Standard Settings
A size standard definition file provides a list of fragment sizes in
base pairs and the dye color associated with a particular size
standard. During peak detection and size-calling, the
GeneMapper&reg; ID-X Software matches an observed fragment peak
from the size standard run with the sample with a corresponding size
in the definition file.
1. Open the GeneMapper ID-X Manager if not already open (see
page 30).
2. In the GeneMapper ID-X Manager, select the Size Standards
tab.
3. Click a table row to select the size standard setting to review,
then click Open.
4. Review the default size standard settings provided using Table 4
on page 46.
5. When you are finished reviewing all size standard settings, click
Done to close the GeneMapper ID-X Manager.
Note: You can also create a new size standard definition using
the GeneMapper ID-X Manager.
Defaults Provided
Table 4
The following default size standard definition files are provided with
the GeneMapper&reg; ID-X Software for analysis of AmpFlSTR&reg; kit
data:
Default size standards
Size Standard
CE_G5_HID_GS500
Description
Includes fragments present in
the GeneScan™ 500 LIZ&reg; size
standard (75 to 450-bp),
excluding the 250-bp
fragment.
When to Use
Use with data generated on ABI PRISM &reg;
310 and 3100 Series Genetic Analyzers,
and Applied Biosystems 3130 Series
Genetic Analyzers, and run with the
GS500 LIZ&reg; Size Standard.
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45
Chapter 2 Setting Up the Software
Step 5: Import Lab Reference and Custom Control Profiles
Table 4
Default size standards (continued)
Size Standard
Description
When to Use
CE_F_HID_GS500
(75-400)
Includes fragments present in
the GeneScan™ 500 ROX™
size standard (75 to 400-bp),
excluding the 250-bp
fragment.
Use with data generated on ABI PRISM &reg;
310 and 3100 Series Genetic Analyzers,
and Applied Biosystems 3130 Series
Genetic Analyzers, and run with the
GS500 ROX™ Size Standard and all
AmpFlSTR&reg; 4-dye kits (except the SGM
Plus&reg; kit).
CE_F_HID_GS500
(75-450)
Includes fragments present in
the GeneScan™ 500 ROX™
size standard (75 to 450-bp),
excluding the 250-bp
fragment.
Use with data generated on ABI PRISM &reg;
310 and 3100 Series Genetic Analyzers,
and Applied Biosystems 3130 Series
Genetic Analyzers, and run with the
GS500 ROX™ Size Standard and the
AmpFlSTR&reg; SGM Plus&reg; kit.
GS600_LIZ
Includes fragments present in
the GeneScan™ 600 LIZ&reg; size
standard (80 to 460-bp).
Use with data generated on ABI PRISM &reg;
310 and 3100 Series Genetic Analyzers,
and Applied Biosystems 3130 Series
Genetic Analyzers, and run with the
GS600 LIZ&reg; Size Standard.
Step 5: Import Lab Reference and Custom Control
Profiles
Overview
In this section, you will import a project that contains analyzed lab
reference samples, custom controls, and QC samples that are used to
illustrate the quality control features of the GeneMapper&reg; ID-X
Software (see Chapter 5). This project has been edited to remove any
off-ladder (OL) labels.
IMPORTANT! Before adding your own lab reference and custom
control samples using the procedure described below, review the
samples manually and edit allele labels as needed to ensure that the
profile is accurate. Profiles that include OL labels are not imported
into the Profile Manager. Profiles that include numeric allele labels
on peaks that are not true DNA peaks will affect concordance results.
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Chapter 2 Setting Up the Software
Step 5: Import Lab Reference and Custom Control Profiles
Importing the
Reference Project
1. Open the GeneMapper ID-X Manager if not already open (see
page 30).
2. In the GeneMapper ID-X Manager, select the Projects tab, then
click Import.
3. Navigate to and select Reference Profile Project.ser, then click
Import.
Note: The reference project file path shown above is for Full
install configurations only. For the reference project file path
for Client install configurations, see “Using the Guide with the
Example Data Provided” on page 18.
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47
Chapter 2 Setting Up the Software
Step 5: Import Lab Reference and Custom Control Profiles
4. Make sure the Practice Security Group is selected, then click
OK.
5. Click Done to close the GeneMapper ID-X Manager.
Adding Profiles to
the Software
Database
1. In the Project window, click
(Open Project).
2. Select Reference Profile Project, then click OK.
3. From the Table Setting drop-down list, select Import
Reference Profiles. The Sample table view changes to display
only those columns required to add reference profiles to the
GeneMapper&reg; ID-X Software database.
Note: All genotypes and edits are saved with the imported
project. This project does not require re-analysis.
4. In the Profile ID column of the Samples tab, click each cell,
then enter the Profile ID names as shown below.
Note: Profiles are stored in the GeneMapper&reg; ID-X Software
database under Profile ID, not Sample Name.
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Chapter 2 Setting Up the Software
Step 5: Import Lab Reference and Custom Control Profiles
5. Select the Analyst A.fsa row, then select ToolsAdd
ProfileLab Reference.
6. Click Close in the Add Profile Results dialog box to save the
assigned lab reference profile to the GeneMapper&reg; ID-X
Software database.
7. Shift-click to select the ID_CustomControl.fsa and
QC_Sample_01.fsa rows, then select ToolsAdd
ProfileCustom Control.
8. Click Close in the Add Profile Results dialog box to save the
assigned custom control profiles to the GeneMapper&reg; ID-X
Software database.
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49
Chapter 2 Setting Up the Software
Step 5: Import Lab Reference and Custom Control Profiles
Viewing Profiles in
the Profile
Manager
1. In the Project window, select ToolsProfile Manager.
2. View the list of profiles in the Profile Manager window. Click
to expand at least one Profile ID to view the genotypes
stored in the GeneMapper&reg; ID-X Software database.
3. Click Close to close the Profile Manager window and return to
the Project window.
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Chapter 2 Setting Up the Software
Step 6: Set the Project Options
Step 6: Set the Project Options
Overview
In This Section
Project Options are user-specific project preferences that allow you
to specify default security and analysis options for your user account.
In this section, you will set the software to:
• Automatically assign a security group (available selections
determined by user account) when you create a project.
• Automatically assign analysis settings when you add samples to
the project.
• Display the Analysis Requirements Summary (ARS) to identify
any conditions that could prevent analysis.
• Automatically disregard low-quality allelic ladders and proceed
with the analysis of run folders containing one or more passing
allelic ladders.
• Display the Analysis Summary, which provides a snapshot of
the analysis status of all samples in the project and the quality
status of allelic ladders, controls, and samples.
Note: These options are suggested for an optimized, efficient data
review workflow. However, you can modify project options as
needed to meet your laboratory workflow requirements.
Setting Project
Options
Project options are associated with the user account currently logged
in to the GeneMapper&reg; ID-X Software (in this example, the Practice
User).
Note: Set project options when you obtain your personal or lab-
specific user account. For more information on the GeneMapper&reg;
ID-X Software security system, see the GeneMapper&reg; ID-X Software
Version 1.0 Administrator’s Guide.
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51
Chapter 2 Setting Up the Software
Step 6: Set the Project Options
1. Select FileProject Options.
2. Complete the Options tabs for the Practice User as described in
Table 5 on page 53, using the GeneMapper&reg; ID-X Software
Help as a guide.
Table 5
Practice User project options settings
Tab
General
52
Settings
Verify the settings as shown below:
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 2 Setting Up the Software
Step 6: Set the Project Options
Table 5
Practice User project options settings (continued)
Tab
Add
Samples
Settings
Enter the settings as shown below:
N
To set a panel for all samples:
• Click in the text field to open
the Select a Panel dialog
• Click
to view the available
AmpFlSTR&reg; panels, then select
the Identifiler_v1X panel
• Click OK to close the dialog
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Chapter 2 Setting Up the Software
Step 6: Set the Project Options
Table 5
Practice User project options settings (continued)
Tab
Analysis
Settings
Click Help at the bottom of the tab to learn more about the options presented in the
Analysis Summary area of this tab, then enter the settings as shown below:
3. Click OK after completing all tabs to close the Options dialog
and return to the Project window.
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GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 3
Creating a Project, Analyzing,
and Reviewing Analysis
Workflow Summaries
This chapter covers:
Chapter 1
Getting Started
■ Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
■ Step 1: Create a Project and Add Samples . . . . . . . . . . . . . . . 56
■ Step 2: View Sample Information and Raw Data . . . . . . . . . . 59
Chapter 2
■ Step 3: Select Analysis Settings and Start Analysis . . . . . . . . 63
Setting Up the Software
■ Step 4: Review the ARS and Correct the Requirements . . . . 64
■ Step 5: Analyze the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
■ Step 6: Review the Analysis Summary. . . . . . . . . . . . . . . . . . 68
Chapter 3
Creating a Project,
Analyzing, and Reviewing
Analysis Workflow
Summaries
Chapter 4
Manually Reviewing and
Interpreting Data
Chapter 5
Performing Quality
Control of Sample
Results
Chapter 6
Performing
Peer/Technical Review of
Electronic Data
Chapter 7
Reporting, Exporting and
Printing Results
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Chapter 3 Creating a Project, Analyzing, and Reviewing Analysis Workflow Summaries
Overview
Overview
During analysis, the GeneMapper&reg; ID-X Software performs the
following tasks, based on the analysis settings and project options set
up in Chapter 3:
•
•
•
•
Analysis requirements check
Data analysis (peak detection and sizing, allele-calling)
Allelic ladder and sample quality assessment
Analysis workflow summary generation
This chapter will demonstrate these tasks using the example data set
provided with the software.
In This Chapter
In this chapter, you will learn how to:
•
•
•
•
•
Create a project and add samples
View sample details
Select analysis settings
Analyze the data
Review the analysis workflow summaries (Analysis
Requirements Summary, Analysis Summary)
Step 1: Create a Project and Add Samples
Creating a
New Project
If a project is already open in the Project window, click
Project).
(New
Note: If you have a previous project open you may be prompted to
save changes. Click Yes.
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Chapter 3 Creating a Project, Analyzing, and Reviewing Analysis Workflow Summaries
Step 1: Create a Project and Add Samples
Adding Samples
from Sample Files
1. In the new Project window, click
(Add Samples to Project).
2. In the Files tab of the Add Samples to Project dialog box,
navigate to the folder containing the example data, select the
Identifiler Samples folder, then click Add to List.
Note: The example data file path shown above is for Full install
configurations only. For the example data file path for Client
install configurations, see “Using the Guide with the Example
Data Provided” on page 18.
3. Click Add. When you add samples from sample (.fsa) files to a
project:
• You specify the location of the .fsa files on the hard drive
or a network drive.
• The sample files remain in their original location on the
drive, and are not stored in the GeneMapper&reg; ID-X
Software project or database.
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Chapter 3 Creating a Project, Analyzing, and Reviewing Analysis Workflow Summaries
Step 1: Create a Project and Add Samples
• The GeneMapper&reg; ID-X Software reads the information it
needs from the .fsa files. No information is written back to
the original sample files.
• The added samples are displayed in the Samples table in
the content pane of the Project window. The run folder
from which you added the samples is displayed in the
navigation pane.
Sample table lists all files in selected run folder (only
one run folder in this example). Analysis settings are
loaded by default as specified in Project Options.
Navigation pane
lists run folders for
added samples
58
Table Setting selected
determines the columns
displayed in the Samples table
indicates samples have
not been analyzed
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 3 Creating a Project, Analyzing, and Reviewing Analysis Workflow Summaries
Step 2: View Sample Information and Raw Data
4. In the Project window, select 31XX Data Analysis from the
Table Setting drop-down list. Only the columns needed for
analysis of ABI PRISM&reg; 3100 Series and Applied Biosystems
3130 Series Genetic Analyzer data are displayed in the Samples
table.
Step 2: View Sample Information and Raw Data
You have access to the following sample information from the
Project window:
• Sample file, analysis and run parameters
• Raw data
• Electrophoresis, power and temperature (EPT) data
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Chapter 3 Creating a Project, Analyzing, and Reviewing Analysis Workflow Summaries
Step 2: View Sample Information and Raw Data
Viewing Sample
Information
1. Click
to expand the Identifiler Samples folder in the
navigation pane, then select the ID_AllelicLadder.fsa sample.
The Info tab for the selected sample is displayed in the content
pane:
The Sample
Information, Error
Message and Last
Used Analysis
Settings areas are
updated each time
you analyze
2. Click the vertical scroll bar at the right of the Info tab window to
review the following sample-specific information presented in
this tab:
Info Type
Info Listed for Selected Sample
Sample
Information
• Sample file name and sample name
• Sample origin path and file source
• Status message indicating any changes made to
the sample in the Samples table
Error Message
• Errors encountered during analysis (if any)
Last Used
Analysis Settings
• Last settings used for analysis
Note: This area will be blank if the sample Status is
(Unanalyzed). After analysis, the settings last
used to analyze the sample file are displayed in this
tab regardless of the analysis settings selected in
the Samples table.
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Chapter 3 Creating a Project, Analyzing, and Reviewing Analysis Workflow Summaries
Step 2: View Sample Information and Raw Data
Info Type
Run Information
Info Listed for Selected Sample
•
•
•
•
•
Instrument user name
Instrument name and Data Collection version
Run date (in yyyy:dd:mm) and time (in hr:min:sec)
Run duration
Total data points
Note: All sample files created during one injection
on a multi-capillary instrument (a set of 4 or 16
capillaries) will have the same run date, run time,
and injection time.
Data Collection
Settings
•
•
•
•
•
•
•
Run voltage and injection voltage (in volts)
Injection duration (in milliseconds)
Laser power (in mW) and temperature (in &deg;C)
Run module and run protocol name
Dye set name
Polymer lot number and expiration date
Results Group name
Note: Results Groups apply to ABI PRISM&reg; 3100
Series Data Collection Software v 2.0 and
Applied Biosystems 3130 Series Data Collection
Software v 3.0 only.
Capillary
Information
• Length and number of capillaries
• Capillary number used for injection
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Chapter 3 Creating a Project, Analyzing, and Reviewing Analysis Workflow Summaries
Step 2: View Sample Information and Raw Data
Viewing Raw Data
You can use the raw data view of a sample to help evaluate any
anomalies, the causes of poor size-calling, and to determine the start
and stop points for analysis.
1. Select the Raw Data tab in the content pane. The raw data plot
for the ID_AllelicLadder.fsa sample is displayed.
2. Select the EPT Data tab in the content pane. The EPT plot is
displayed.
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Chapter 3 Creating a Project, Analyzing, and Reviewing Analysis Workflow Summaries
Step 3: Select Analysis Settings and Start Analysis
3. Select the Project node in the navigation pane to return to the
Samples table view.
Step 3: Select Analysis Settings and Start Analysis
Analysis settings include the Analysis Method, Size Standard, Panel,
and Sample Type selections needed to perform analysis. Based on
the Project Options you set in Chapter 2, the samples you added to
the Samples table automatically have analysis settings specified.
Selecting Analysis
Settings
Note: In this section, you will intentionally alter some of the
analysis settings in the Samples tab to trigger the display of the ARS
when you start the analysis.
1. In the Project window, make sure 31XX Data Analysis is
selected from the Table Setting drop-down list.
2. Enter the Samples tab analysis settings as shown below:
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Chapter 3 Creating a Project, Analyzing, and Reviewing Analysis Workflow Summaries
Step 4: Review the ARS and Correct the Requirements
Starting Analysis
Click
(Analyze).
When analysis is started, the software identifies any conditions that
may prevent analysis or cause unexpected results, sets a
flag for
Analysis Requirements Not Met (ARNM) PQV and displays the
ARS if chosen in the Project Options. In this example, we have
chosen to display the ARS.
The Analysis Requirements Summary dialog box opens because at
least one sample in the project does not meet one or more analysis
requirements.
Step 4: Review the ARS and Correct the
Requirements
Reviewing the
ARS
From the ARS, you may view the samples that do not meet the
analysis requirements or you can continue with analysis. In this
section, you will view the flagged samples in the example project.
1. Keep the default selection in the What would you like to do
next? area of the ARS, then click OK.
The Samples table opens. If one or more analysis requirements
are not met, the ARNM PQV is set to
. Based on the analysis
settings changes you made in step 2 on page 63, note that only
the allelic ladder samples in the example project are listed with
a
ARNM flag in the Samples table.
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Chapter 3 Creating a Project, Analyzing, and Reviewing Analysis Workflow Summaries
Step 4: Review the ARS and Correct the Requirements
Samples tab label
indicates table is filtered
bold italics indicates
table is filtered
Check
ARNM PQV
When you view the Samples table from the ARS, the Samples
table is filtered. The current table setting is applied to determine
which columns are displayed, but only the samples in the
category selected are listed. In this example, samples that do not
meet the analysis requirements are listed. The filtered condition
of the table is indicated by the status of the Samples tab label
(filtered) and the Table Setting label (bold italics).
2. Place the pointer over a
ARNM flag to display a tooltip with
analysis requirement information for each sample in the filtered
Samples table.
Note that the analysis Status for the samples is still
(Unanalyzed).
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Chapter 3 Creating a Project, Analyzing, and Reviewing Analysis Workflow Summaries
Step 5: Analyze the Data
Correcting the
Analysis
Requirements
To correct the unmet requirements listed in the ARS, change the
analysis settings in the Samples table back to their original values:
1. Change the Analysis Method for the first Ladder sample to
Getting Started.
2. Change the Size Standard for the second Ladder sample to
CE_G5_HID_GS500.
The updated Samples table analysis settings should be:
Step 5: Analyze the Data
Analyzing the
Data
In this section, you will analyze with all analysis requirements
satisfied and display the Analysis Summary.
1. Click
(Analyze).
2. Complete the fields in the Save Project dialog box:
a. For Name, type Getting Started &lt;your initials&gt;. For
example, Getting Started AB.
b. Verify that the Practice Security Group is selected from the
drop-down list.
c. Click OK to save the project to the GeneMapper&reg; ID-X
Software database and start analysis.
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Chapter 3 Creating a Project, Analyzing, and Reviewing Analysis Workflow Summaries
Step 5: Analyze the Data
Viewing Analysis
Progress
After saving the project to the database:
• The project name (entered in step 2a on page 66) appears in the
title bar of the Project window. For example:
• The software then begins analysis.
Note the following after analysis begins:
• Allelic ladder sample types are analyzed before all other sample
types in the project. The sample currently being analyzed is
highlighted in green in the Samples table:
• Analysis progress is displayed at the bottom of the Project
window:
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67
Chapter 3 Creating a Project, Analyzing, and Reviewing Analysis Workflow Summaries
Step 6: Review the Analysis Summary
Step 6: Review the Analysis Summary
About the
Analysis
Summary Tab
Based on the Project Options you set in Chapter 2, the Analysis
Summary tab is displayed when analysis is complete.
For efficient data evaluation, the Analysis Summary tab:
• Provides a summary of the analysis status for all or a subset of
samples in the project
• Displays an overview of allelic ladder, control, and sample
quality
• Visually separates passing samples from samples that do not
meet one or more quality thresholds
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Chapter 3 Creating a Project, Analyzing, and Reviewing Analysis Workflow Summaries
Step 6: Review the Analysis Summary
• Provides interactive links to specific categories of samples
(passing/check/low quality, allelic ladder/control/sample)
IMPORTANT! Refer to your own laboratory protocol to determine
the samples (allelic ladder, positive control, negative control, custom
control, and unknown) that require manual review when analyzing
data generated in your laboratory.
Briefly review the features and areas of the Analysis Summary tab as
described below, then continue to Chapter 4, where you will review
the functions of this tab in more detail.
Features of the
Analysis
Summary Tab
Note the following features of the Analysis Summary tab:
• You can display an Analysis Summary for the entire project or
for an individual run folder in the project by selecting a run
folder from the drop-down list at the top of the tab
Note: If the project contains only one run folder, this selection
is dimmed.
In this example, Identifiler Samples is the only run folder in the
Getting Started project:
• Blue links take you to a Samples table displaying only the
samples of interest
Click to display a
Samples table
displaying only the
allelic ladder samples
Click to display a Samples
table with only allelic
ladders that did not meet
one or more requirements
• Tooltips explain symbols
Place the pointer over symbols to display tooltips
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Chapter 3 Creating a Project, Analyzing, and Reviewing Analysis Workflow Summaries
Step 6: Review the Analysis Summary
Areas of the
Analysis
Summary Tab
Analysis Status
The Analysis status area at the top of the Analysis Summary tab
indicates that all samples in the Getting Started project are analyzed.
Allelic Ladder Quality
The Allelic Ladder Quality area indicates that of the two allelic
ladder samples analyzed in the Getting Started project, one met all of
).
the allelic ladder quality requirements ( ) and one did not (
You can use the allelic ladder quality results to determine the
samples that require manual review. For example, if each run folder
contains at least one passing allelic ladder and the positive and
custom controls meet all quality value thresholds, visual inspection
of the allelic ladders may not be required. Depending on validation,
you can proceed directly to evaluation of the controls or samples in
the project.
Control Quality
The Control Quality area of the Analysis Summary indicates that of
the three controls analyzed in the Getting Started project, the positive
and custom controls met all quality thresholds ( ) and generated
the expected profile, but the negative control did not.
When validated, this area of the Analysis Summary may eliminate
the need for you to visually inspect the control samples if they fall
under the green All Thresholds Met column. Controls in this column
have met all sample-level and marker-level quality values, including
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Chapter 3 Creating a Project, Analyzing, and Reviewing Analysis Workflow Summaries
Step 6: Review the Analysis Summary
Control Concordance (CC). This means that the sample genotypes
for positive and custom controls match the expected known profile
without any anomalies. For negative controls, this means that there
were no peaks detected above the peak amplitude threshold.
You can also use the control quality results to verify allelic ladder
quality. For example, allelic ladders may meet all requirements, but if
their migration rate differs from the sample migration rate, samples
and controls may contain OL calls. However, controls that met all
thresholds (and therefore do not contain OL calls), may indicate
consistent migration rates for allelic ladders and samples.
Sample Quality
The Sample Quality area of the Analysis Summary indicates that of
the eight samples analyzed, four met all quality thresholds ( ) and
four did not (
).
In Chapter 4, you will use the blue links to visually inspect certain
categories of samples.
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Chapter 3 Creating a Project, Analyzing, and Reviewing Analysis Workflow Summaries
Step 6: Review the Analysis Summary
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GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 4
t
Manually Reviewing and
Interpreting Data
This chapter covers:
Chapter 1
Getting Started
■ Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
■ Step 1: Examine Allelic Ladder Quality. . . . . . . . . . . . . . . . . 74
■ Step 2: Examine Control Quality . . . . . . . . . . . . . . . . . . . . . . 83
Chapter 2
■ Step 3: Examine Sample Quality . . . . . . . . . . . . . . . . . . . . . . 88
Setting Up the Software
■ Step 4: Review the Low-Quality Sample Results . . . . . . . . . . 90
■ Step 5: View Additional Plot Settings . . . . . . . . . . . . . . . . . 129
■ Step 6: Delete Samples from the Project . . . . . . . . . . . . . . . 133
Chapter 3
Creating a Project,
Analyzing, and Reviewing
Analysis Workflow
Summaries
■ Step 7: Save the Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
Chapter 4
Manually Reviewing and
Interpreting Data
Chapter 5
Performing Quality
Control of Sample
Results
Chapter 6
Performing
Peer/Technical Review of
Electronic Data
Chapter 7
Reporting, Exporting and
Printing Results
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
73
Chapter 4 Manually Reviewing and Interpreting Data
Overview
Overview
The Analysis Summary discussed in Chapter 3 guides you directly to
different types of samples while following a logical data
interpretation workflow, regardless of whether the software is being
used as an expert system or not. In a traditional manual review
workflow, you would most likely visually inspect all unknown
sample electropherograms. In a validated expert system workflow,
you would only view those samples that did not meet one or more
quality value thresholds.
Note: Refer to your own laboratory protocol to determine the
controls and samples that require manual review.
In This Chapter
In this chapter, you will review the example data analyzed in
Chapter 3 and learn how to:
• Use the Analysis Summary tab and filtered Samples table to
examine allelic ladder, control and sample quality
• Investigate sample-level PQVs, and marker-level PQVs using
the QVD pane
• Review sample plots and edit peak labels
• Adjust plot displays to determine the source of artifacts
Note: Some steps performed in this chapter are included only to
demonstrate the use of certain features in the GeneMapper&reg; ID-X
Software and may not be a part of your routine analysis workflow.
Step 1: Examine Allelic Ladder Quality
Overview
74
The order of information displayed in the Analysis Summary is
designed to direct you to evaluate the allelic ladder quality first. The
designation is based on a set of allelic ladder requirements. If there is
at least one passing allelic ladder per run folder and the positive and
custom controls meet all quality value thresholds as displayed in the
Analysis Summary, you may not require visual inspection of the
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 4 Manually Reviewing and Interpreting Data
Step 1: Examine Allelic Ladder Quality
allelic ladders and may proceed directly to evaluation of the controls
or samples in the project (depending on validation). However, for the
purposes of this guide, you will walk through the process for
manually reviewing allelic ladder samples.
Viewing Allelic
Ladder Quality
Status
In Chapter 3, the Allelic Ladder Quality area of the Analysis
Summary tab indicates that of the two allelic ladder samples
analyzed, one has met all allelic ladder requirements ( ) and one
has not (
).
Note: Low-quality (
) allelic ladders are not used to create bin
offsets.
Examining the
Low-Quality
Allelic Ladder
1. If the Getting Started project is not already open, click
(Open Project) in the Project window.
Note: If you have a previous project open you may be prompted
to save changes. Click Yes.
2. In the Open Project window, select the Getting Started &lt;your
initials&gt; project, then click OK. The Getting Started project
opens in the Project window.
3. In the Samples table, verify that 31XX Data Analysis is
selected from the Table Setting drop-down list.
4. Verify that the Analysis Summary tab is selected in the content
pane.
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Step 1: Examine Allelic Ladder Quality
5. In the Allelic Ladder Quality area of the Analysis Summary tab,
click the link for the
allelic ladder sample.
The filtered Samples table displays the selected sample. Note
that this low-quality allelic ladder sample has a
CGQ PQV.
Low Quality
CGQ PQV
6. Select the Ladder sample in the filtered Samples table, then
click
(Display Plots). The plot for the selected allelic ladder
sample opens in the Samples plot.
7. Click
(Maximize) in the top-right corner of the Samples
plot to maximize the display.
8. Select Data Interpretation from the Plot Setting drop-down
list.
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Based on the display options of this default plot setting (see
Chapter 2), the Samples plot displays:
• Two electropherogram (dye) panes in a single view
• Each pane zoomed to the 75 - 450 base pair range
• Each of four dyes (blue, green, yellow, red) in a separate
pane
• The Genotypes table and QVD pane displayed under the
electropherograms
Electropherogram
(dye) panes
Genotypes table
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QVD pane
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Step 1: Examine Allelic Ladder Quality
Note the appearance of the marker headers and bins:
Marker header colors
correspond to GQ flag color
Virtual (pink) bin
Physical (gray) bin
The marker headers are color-coded (green, yellow, red) to
reflect the GQ flag color. Bins are displayed according to bin
type (see Chapter 2), with virtual bins in pink and physical bins
in gray.
Note: For more information on virtual and physical bins, see
the GeneMapper&reg; ID-X Software Version 1.0 Reference Guide.
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Step 1: Examine Allelic Ladder Quality
9. To investigate the reason why a particular marker failed the
allelic ladder quality assessment, click the red D8S1179 marker
header in the blue dye pane to display quality assessment
information in the QVD pane for this marker.
Note: The columns displayed in the Genotypes table are
determined by the table setting selected in the Project window.
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Step 1: Examine Allelic Ladder Quality
The QVD pane displays the allelic ladder quality requirement
that was not met for the selected marker. In this example, one or
more of the expected allelic peaks fell below the peak amplitude
threshold set for the D8S1179 marker.
10. Click the vertical scroll bar at the right of Samples plot until you
can see the D5S818 marker in the red dye pane.
Click the scroll bar
to display the next
electropherogram
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Step 1: Examine Allelic Ladder Quality
11. Click the green D5S818 marker header to display the quality
assessment details for this marker.
The QVD pane indicates that all allelic ladder quality
requirements are met for the selected marker. Based on the
calculated GQ values shown in the QVD pane, this marker is
flagged as Passing quality ( ). However, since one or more
markers within this allelic ladder sample do not meet all quality
requirements, the allelic ladder is classified as Low Quality
( ) and it will not be used to create bin offsets.
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Step 1: Examine Allelic Ladder Quality
12. Click
(No Table) in the Samples plot toolbar to hide the
Genotypes table and QVD pane, and view only the dye panes.
Note: This toolbar selection does not alter the selected plot
settings.
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Step 2: Examine Control Quality
13. Select 4 from the Panes drop-down list to display all dyes in the
Samples plot.
While this particular ladder would not be usable (since several
expected peaks are missing), if another ladder had broad peaks
or a spike but was still genotyped accurately, you may override
CGQ for the ladder, which will then automatically apply the bin
offsets from that ladder. This procedure is recommended only if
you do not have another passing ladder.
14. Select FileClose Plot Window to return to the Project
window.
Step 2: Examine Control Quality
Overview
Viewing Control
Quality Status
In this section, you will use the features of the Analysis Summary tab
and the Samples plot to manually verify the quality of the control
samples analyzed in the Getting Started project in Chapter 3.
Select the Analysis Summary tab in the Project window.
In Chapter 3, the Control Quality area of the Analysis Summary tab
indicates that of the three control samples analyzed, two were of
Passing quality ( ) and one was of Low Quality (
).
If a control has met all thresholds, the expected profile was obtained
with no other anomalies detected. Therefore, you may not be
required to visually inspect the control samples. However, the next
two sections demonstrate how to manually review the control
samples.
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Step 2: Examine Control Quality
Examining a
Passing
Control
1. In the Control Quality area of the Analysis Summary tab, click
the link for the
Custom Control sample.
The filtered Samples table displays the selected sample. Note
that all sample-level PQVs for this custom control sample
are
.
2. Select the ID CustomControl sample in the filtered Samples
table, then click
(Display Plots). The plot for the selected
custom control sample opens in the Samples plot.
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Step 2: Examine Control Quality
3. To investigate the quality of this control sample, click the
vertical scroll bar at the right of the Samples plot to scroll
through all panes. Note that all of the marker headers are
colored green, which indicates that this custom control sample
has met all marker-level PQV thresholds.
Note: For traditional manual review, if you are required to
visually inspect the control samples (not rely solely on PQVs),
the color-coded marker headers may help reduce the amount of
time spent on this task. If all markers are green, you know that
this control produced the expected profile and no other
anomalies were detected. If a marker header is yellow or red,
you know those are the markers where anomalies were detected.
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Step 2: Examine Control Quality
4. Click the green D8S1179 marker header in the blue dye pane to
display the quality assessment details for this marker. Based on
the calculated GQ value shown in the QVD pane, this marker is
flagged as Passing quality ( ).
Passing CC PQV
Note the
CC PQV, indicating that this marker contains the
expected genotype for that marker.
Note: The profile for each sample in the project designated as a
custom control is compared against the custom positive control
profile stored in the Profile Manager. You added the CUSTOM
CONTROL profile ID to the Profile Manager in Chapter 2.
5. Select FileClose Plot Window to return to the Project
window.
Examining a
Low-Quality
Control
1. Select the Analysis Summary tab in the Project window.
2. In the Control Quality area of the Analysis Summary tab, click
the link for the
Negative Control sample.
The filtered Samples table displays the selected sample. Note
that this negative control sample shows a
CGQ PQV.
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Step 2: Examine Control Quality
3. To investigate the anomalies detected in this sample, select the
NegControl sample in the filtered Samples table, then click
(Display Plots). The plot for the selected negative control
sample opens in the Samples plot. Note that several of the
marker headers are colored red and there are peaks detected in
the sample.
4. Click the red D8S1179 marker header in the blue dye pane to
display the quality assessment details for this marker. Based on
the calculated GQ value shown in the QVD pane, this marker is
flagged as Low Quality (
).
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Step 3: Examine Sample Quality
Check CC PQV
Note the
CC PQV for this marker, indicating that this
marker does not contain the expected result. Since peaks are
detected in several markers of this negative control, this
negative control is flagged as low quality.
Note: You will use the Profile Comparison tool in Chapter 5 of
this guide to help determine the possible contributor to this
negative control profile.
5. Select FileClose Plot Window to return to the Project
window.
Step 3: Examine Sample Quality
Overview
Viewing Sample
Quality Status
In this section, you will use the features of the Analysis Summary tab
and the Samples plot to manually verify the quality of the unknown
samples analyzed with the Getting Started project in Chapter 3.
Select the Analysis Summary tab in the Project window.
In Chapter 3, the Sample Quality area of the Analysis Summary tab
indicates that of the eight samples analyzed, four met all quality
thresholds ( ) and four did not (
).
For the purposes of this guide, you will examine only those samples
that did not meet one or more thresholds. Examination of passing
samples would follow the same workflow.
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Step 3: Examine Sample Quality
Examining the
Low-Quality
Samples
1. In the Sample Quality area of the Analysis Summary tab, click
the link for the
Samples.
2. The filtered Samples table displays the selected samples. Note
the
and
sample-level PQVs for these low-quality
samples.
From the sample-level PQVs shown, you can conclude that:
• Sample 05 contains a spike (
SSPK) within a marker
size range or another minor anomaly within the marker
size range was detected in addition to spike between two
markers (
CGQ)
• Sample 06 is a potential mixture (
MIX)
• Sample 07 has a
SQ, which indicates there is a
resolution issue or a problem with the size standard peak
detection
• Sample 08 contains an unexpected peak in between two
markers (
OMR) and other anomalies within one or
more marker size ranges (
CGQ)
Follow the procedures outlined in “Step 4: Review the LowQuality Sample Results” on page 90 to individually review the
quality of these unknown samples.
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Step 4: Review the Low-Quality Sample Results
Step 4: Review the Low-Quality Sample Results
Examining the
SQ Sample
Results
A
SQ PQV indicates that the sizing quality is below the passing
range specified in the analysis method. This example illustrates:
• How to view SQ using the Size Match Editor
• The SQ PQV flag
To examine a
SQ PQV:
1. Select Sample 07 in the Samples table, then click
(Size
Match Editor) to view the peak assignments for the size
standard peaks in this sample.
Peak(s) exceed Broad
Peaks (BD) threshold
90
Calculated SQ value
in Check range
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Step 4: Review the Low-Quality Sample Results
Note the following in the Size Match Editor:
• All size standard peaks are present and labeled correctly, as
compared to the fragment sizes stored in the
CE_G5_HID_GS500 size standard definition file set for
this sample
• The calculated SQ value, 0.4167 for this sample, is within
the Check ( ) range set in the analysis method (default
value = 0.74 – 0.26)
• A “Broad Peak(s) Detected” message indicates there are
peaks present in this sample that exceed the Broad Peak
(BD) Max Peak Width threshold set in the analysis method
In this example, the SQ is
due to the broad peaks.
Note: For more information on the calculation of SQ, see the
GeneMapper&reg; ID-X Software Version 1.0 Reference Guide.
2. Click OK to close the Size Match Editor.
Displaying the
Low-Quality
Sample Plots
1. Shift-click to select all samples in the filtered Samples table,
then click
(Display Plots).
2. Verify that Data Interpretation is selected from the Plot
Setting drop-down list.
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3. The plots for all of the selected samples are shown in the
Samples plot.
The first two panes display the blue dye and green dye for the
first sample selected in the Samples table (in this example,
Sample 05).
Note: The selection order in the Samples table determines the
display order in the Samples plot.
Examining the
SSPK Sample
Results
A
SSPK (Sample Spike) PQV indicates that one or more spike
peaks have been detected within a marker range or between two
markers. This example illustrates:
• Automatic labeling of spikes
• The Marker Spike (SPK) and Peak Height Ratio (PHR) PQV
flags
• How to confirm a spike in raw data
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• How to override GQ
• How to override CGQ
To investigate a marker with a yellow or red marker header bar:
1. Click the yellow D2S1338 marker header in the green dye pane
of Sample 05 to display the quality assessment details for this
marker.
Check PHR and SPK PQVs
Note the following:
• There is a peak labeled as “Spike” present in this marker
and the marker-level
SPK PQV is triggered, indicating
that one or more spikes are detected within the marker size
range (in this case, one spike was detected)
Note: This peak is automatically labeled as a Spike artifact
and displayed with a pink label border by the
GeneMapper&reg; ID-X Software. Peaks labeled as artifacts
are not considered true alleles by the software and are not
listed in the Genotypes table.
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• The marker-level
PHR PQV is also triggered for this
marker, indicating that the peak height ratio calculated
between the lowest and highest allele peaks within the
marker is less than the Min Peak Height Ratio threshold
defined in the analysis method (in this example, 0.7)
2. Click-drag the Size column margin in the QVD pane to the right
to expand its contents and view the peak sizes contributing to
the
PHR and SPK PQVs for this marker.
Click-drag column
margin to resize
Calculated
Calculated
peak
PHR
positions (bp) threshold
PHR
threshold
defined in
Analysis
Method
GQ Weighting
defined in
Analysis
Method
Note: The SPK and PHR PQV status are used to determine the
GQ PQV. Based on the calculated GQ value shown in the QVD
pane, this marker is flagged as Check ( ).
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3. In the green dye pane, left-click the Spike artifact label to select
the peak, then right-click the label to open a drop-down menu
containing peak edit actions.
IMPORTANT! You must left-click the label before you
right-click the label.
4. To confirm the spike peak, select Peak Raw Data from the
drop-down menu to open the raw data plot for this peak in the
Project window.
5. To view the raw data plot, click the GeneMapper&reg; ID-X Getting Started &lt;your initials&gt; taskbar button.
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Step 4: Review the Low-Quality Sample Results
6. Review the raw data and peak morphology to confirm that the
selected peak is a spike.
Note: Once you have validated the spike detection PQVs using
your own data, you may not be required to view the raw data to
confirm a spike peak.
7. To return to the Samples plot, click the Getting Started &lt;your
initials&gt; : Samples Plot taskbar button.
8. Right-click the
GQ PQV in the D2S1338 marker row
highlighted in the Genotypes table.
Right-click PQV
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9. Click Yes in the dialog box to override the genotype quality for
this marker.
Note that after overriding:
• The GQ PQV changes to
• All other PQVs for the marker turn gray and maintain their
original shape (
) to indicate that the marker has
been overridden
• The marker header turns green
Note: Overriding GQ allows you to manually accept the
genotype for a particular marker and also provides evidence that
the marker was visually inspected by the analyst.
10. To accept the entire sample profile for Sample 05, you can
override its
CGQ PQV. To do so, first right-click the
CGQ PQV for Sample 05 in the genotypes header of the
Samples plot.
Right-click PQV
The next dialog box displays a message indicating that there are
still
or
marker-level GQ PQVs present in this sample.
Unless you have viewed the rest of the markers and confirmed
the genotypes, you should not continue with the CGQ override.
Click No to return to the Samples plot and confirm the
genotypes for the remaining markers.
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Step 4: Review the Low-Quality Sample Results
11. Click the vertical scroll bar at the right of the Samples plot to
scroll through the two remaining dye panes (yellow and red) for
Sample 05. Note that there is a yellow D5S818 marker header in
the red dye pane. It was this marker that triggered the Override
CGQ warning message seen in step 10 on page 97.
12. Click the yellow D5S818 marker header to display the quality
assessment details for this marker.
Note the marker-level
PHR PQV in the Genotypes table for
this marker. Based on the calculated PHR value shown in the
QVD pane, this marker is flagged as Check ( ).
13. Right-click the
GQ PQV in the highlighted row of the
Genotypes table, then click Yes in the dialog box to override the
genotype quality for this marker.
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14. Now that all GQ PQVs are
for Sample 05, click Yes in the
next dialog box to override the CGQ for this sample.
Note that after overriding, the CGQ PQV changes to
(Manually Overridden).
Note: Overriding CGQ allows you to manually accept the
entire profile for a particular sample and also provides evidence
that the sample was visually inspected by the analyst.
You have now completed reviewing Sample 05. Another use for
CGQ override will be demonstrated in Chapter 6 for review
purposes.
Examining the
MIX Sample
Results
A
Mixed Source (MIX) PQV indicates a potential mixed-source
sample. This example illustrates:
• How to select peaks and view their calculated peak height ratios
• The marker-level PQVs triggered in mixed samples
• The PHR and Allele Number (AN) PQV flags
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Step 4: Review the Low-Quality Sample Results
To investigate the cause of the yellow MIX PQV flag:
1. Click the vertical scroll bar at the right of the Samples plot until
you can see the first two dye panes (blue and green) for
Sample 06.
2. Click the yellow D8S1179 marker header in the blue dye pane
to display the quality assessment details for this marker.
Note the marker-level
PHR PQV in the Genotypes table for
this marker. Based on the calculated PHR value shown in the
QVD pane, this marker is flagged as Check ( ).
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3. Ctrl-click the 17 and 20 allele peaks in the green dye pane for
marker D2S1338 to select them both. The software
automatically calculates a peak height ratio (PHR) value for the
selected peaks and displays the results in the status bar at the
bottom of the Samples plot.
Ctrl-click
two peaks
Calculated PHR for selected
peak pair is shown here
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PHR and AN PQV details
are shown here
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Step 4: Review the Low-Quality Sample Results
Note the following:
• The calculated PHR is less than the minimum PHR
threshold of 0.7 specified in the analysis method
• The
AN PQV in the Genotypes table for this marker,
indicating the number of alleles detected is greater than the
Max Expected Alleles defined in the analysis method
Note: The AN and PHR PQV status is used to determine the
GQ PQV. Based on the observed AN and PHR values shown in
the QVD pane, this marker is flagged as Low Quality (
).
4. Repeat step 3 on page 101 for any of the other peak pairs in this
sample.
You have now completed reviewing Sample 06. This sample
was expected to be from a single source. You will use the
Profile Comparison tool in Chapter 5 to help determine the
potential contributor(s) to this mixture.
Note: For more information on the conditions that must be met
for a sample to be considered a potential mixture, see the
GeneMapper&reg; ID-X Software Version 1.0 Reference Guide.
Examining the
SQ Sample
Results
102
This example illustrates:
•
•
•
•
•
How to view PQV trigger labels
The Broad Peak (BD) PQV flag
How to delete allele labels for a sample
How to add a reason for change to the audit trail
How to mark a sample for deletion from the project
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Chapter 4 Manually Reviewing and Interpreting Data
Step 4: Review the Low-Quality Sample Results
To investigate this low-quality sample:
1. Click the vertical scroll bar at the right of the Samples plot until
you can see the first two dye panes (blue and green) for
Sample 07.
Note: This is the same sample you viewed using the Size Match
Editor earlier in this chapter (see “Examining the SQ Sample
Results” on page 90).
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Step 4: Review the Low-Quality Sample Results
2. In the Samples plot toolbar, click
(PQV Trigger Peak) to
add PQV suffixes to peak labels for peaks that cause any of the
following
PQVs: LPH, MPH, BD, OS.
Note: Displaying the PQV trigger peak labels can help you
quickly find the exact peaks that triggered specific PQV flags.
In this example, (BD) is appended to the label of each peak that
exceeds the Max Peak Width threshold.
3. Click
labels.
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(PQV Trigger Peak) again to turn off the PQV trigger
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Step 4: Review the Low-Quality Sample Results
4. Click the red D3S1358 marker header to display the quality
assessment details for this marker. Note the marker-level
BD
PQV in the Genotypes table, and the Max Peak Width threshold
and observed values related to this PQV in the QVD pane.
Check BD PQV for
selected marker
Observed Max Peak Width
values and accepted
thresholds are shown here
The genotype profile for this sample is not reliable and should
not be reported. Therefore, from the Samples plot, you can
choose to:
• Delete all labels for a sample
or
• Mark the sample for deletion from the project
The following steps 5 through 8 demonstrate these two options.
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5. To delete all labels for Sample 07, right-click in any pane for
this sample, then select Delete All Labels for Sample.
6. Click Yes in the Delete All Labels dialog box.
7. Enter Bad injection in the Reason(s) for Change dialog box
(recorded in the audit trail), then click OK.
Note: By default, a reason for change audit trail entry is
required for all label edits.
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Note that after deleting all allele labels for Sample 07:
• All sample-level and marker-level PQVs for the sample
turn gray and maintain their original shapes (
) to
indicate that the sample has been edited
• Affected marker header colors change to gray
• The sample will still be listed in the Samples and
Genotypes table, but no allele values are reported
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8. To delete Sample 07 from the Getting Started project, select
Mark Sample for Deletion at the top right of any dye pane for
this sample.
Note: The remaining panes associated with this sample are
automatically marked for deletion by the software.
The sample will be deleted from the project when the Samples
plot is closed. For now, keep the Samples plot open to continue
reviewing the last low-quality sample results in this project.
You have now completed reviewing Sample 07.
Examining the
OMR Sample
Results
A
Outside Marker Range (OMR) PQV indicates that one or more
peaks were detected between two marker size ranges specified in the
panel for the marker. This example illustrates:
• Automatic labeling of OMR peaks
• The Out of Bin Allele (BIN), Low Peak Height (LPH), and Max
Peak Height (MPH) PQV flags
• How to change an artifact label to an allele label and assign it to
a selected marker
• How to save a custom artifact label for future use
• How to change an allele label to an artifact label
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To investigate the source of the OMR peak and other potential
anomalies:
Click the vertical scroll bar at the right of the Samples plot until you
can see the last two dye panes (yellow and red) for Sample 08.
Note the following:
• There is a peak labeled OMR present between the vWA and
TPOX markers
• The marker header for TPOX is yellow
• The marker headers for D5S818 and FGA are red
• There is a peak labeled OL present in the D5S818 marker
• There are three labeled peaks present in the FGA marker
Follow the procedures in the following sections (on pages 110 to
128) to individually review the quality of these markers.
You will first investigate the OMR peak between vWA and TPOX
and the quality of the TPOX marker.
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Step 4: Review the Low-Quality Sample Results
To examine TPOX marker and OMR peak:
1. In the Samples plot toolbar, click
(PQV Trigger Peak) to
add PQV suffixes to peak labels for peaks that cause any of the
following
PQVs: LPH, MPH, BD, OS.
MPH suffix
LPH suffix
In this example, (MPH) in TPOX and (LPH) in D5S818 are
appended to the label of each peak that does not meet the
thresholds related to these PQVs set in the analysis method.
2. Click
labels.
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(PQV Trigger Peak) again to turn off the PQV trigger
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Step 4: Review the Low-Quality Sample Results
3. Click the yellow TPOX marker header to display the quality
assessment details for this marker. Note the marker-level
MPH PQV in the Genotypes table for this marker, and the Max
Peak Height threshold (in RFU) and observed values related to
this PQV in the QVD pane.
Check MPH PQV
for selected marker
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Observed Max Peak Height
values and accepted
thresholds are shown here
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4. With the TPOX marker header still selected, left-click the OMR
label.
Note: This peak is automatically labeled as an OMR artifact by
the GeneMapper&reg; ID-X Software. Peaks labeled as artifacts are
not listed in the Genotypes table. In some rare cases, an OMR
artifact peak may be a true allele; you may need to verify the
classification of an OMR peak if you encounter one in your own
data.
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For this example, you will assume that this OMR artifact peak is
indeed a true allele solely to learn how to add an allele label to
an artifact peak and assign it to a selected marker (although you
are aware this is not a true DNA peak).
5. Right-click the OMR label, then select Add Allele Label.
6. In the Add Custom Allele Label dialog box, enter &lt; 6, then click
OK. Note that the TPOX marker is selected for this allele since
this was the marker selected before adding the allele.
.
Note: This custom allele will be added to the TPOX marker and
entered as an allele in the Genotypes table.
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7. In the Reason(s) For Change dialog box, enter Microvariant
OMR, then click OK.
Note that after editing:
• All sample-level PQVs (except SQ) for the sample turn
gray (
) to indicate that the sample has been edited
• All marker-level PQVs for the marker turn gray and
maintain their shape (
), to indicate that the marker
has been edited
• The allele is listed in the Genotypes table
• The allele label changes text and color from pink to black
• The marker header color changes from yellow to gray
(pink if selected)
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Sample PQVs (except SQ) turn
gray, but keep original shape
&lt; 6 allele entered
in Genotypes table
Marker PQVs turn gray,
but keep original shape
8. Select the TPOX marker row in the Genotypes table, then rightclick its
GQ PQV.
9. Click Yes in the dialog box to override the genotype quality and
manually accept the current genotype (&lt;6, 8) for the TPOX
marker. The GQ PQV changes to
and the marker header
turns green.
You have completed reviewing the TPOX marker. You will now
investigate the OL peak present in the D5S818 marker.
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Step 4: Review the Low-Quality Sample Results
To examine the cause of an extra peak:
1. In the red dye pane for Sample 08, place the pointer next to the
X-axis below the red D5S818 marker header until the pointer
changes to a
.
2. Click-drag the pointer to the right to create a box that includes
the area to the left of the D5S818 marker, then release to zoom
in on this marker, as shown below.
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3. Click the red D5S818 marker header to display the quality
assessment details for this marker. Note the marker-level
BIN PQV in the Genotypes table for this marker.
Note: A
BIN PQV indicates that one or more labeled peaks
are detected outside an offset bin. These peaks are automatically
labeled as OL peaks by the software. For information on bin
offsetting, see the GeneMapper&reg; ID-X Software Version 1.0
Reference Guide.
4. Click the OL peak label to select the OL peak.
5. Click
(Combine Dyes) in the Samples plot toolbar to
display all dye colors for the sample in one pane.
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6. Place the pointer next to the Y-axis until the pointer changes to a
, then right-click and select Zoom to.
7. Enter 1000 in the Y-Axis Zooming dialog box, then click OK to
zoom in on the OL peak. Note that the red OL peak is located
under a larger blue dye peak.
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8. Ctrl-click the overlaying blue dye peak to select it (the red OL
peak should still be highlighted).
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Step 4: Review the Low-Quality Sample Results
9. Click
(Sizing Table) in the Samples plot toolbar to display
the Sizing table, which contains the following peak sizing
information for all detected peaks in the sample: size (in base
pairs), peak height, peak area, and data point.
Note: The columns displayed in the Sizing table are determined
by the plot setting selected in the Samples plot.
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10. With the blue dye and red OL peaks still selected, press Ctrl+G
to display only the selected peaks in the Sizing table.
The sizing data indicates that the red OL peak could be caused
by spectral pull-up.
You will change the software-generated OL peak label to a
custom artifact label in the next steps.
To change the OL peak label to a custom artifact label:
1. Select the
D5S818 row in the Sizing table to deselect the
overlaying blue dye peak (the red OL peak should still be
highlighted).
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Step 4: Review the Low-Quality Sample Results
2. Click
(Separate Dyes) in the Samples plot toolbar to display
each dye color for the sample in separate panes.
3. Click
(Genotypes Table) in the Samples plot toolbar to
replace the Sizing table with the Genotypes table and QVD
pane.
4. Left-click the OL peak label in the red dye pane, then rightclick the label and select Rename Allele LabelCustom
Artifact Label.
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5. Complete the Custom Artifact Label dialog box:
a. Enter SPU &lt;your initials&gt; (for example, SPU AB).
b. Select Add to predefined list.
c. Click OK.
Note: This option allows you to select this custom artifact label
from a list of labels in the future.
6. In the Reason(s) For Change dialog box, enter Pull-up, then
click OK.
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Step 4: Review the Low-Quality Sample Results
Note that after editing:
• The SPU artifact label is displayed with a pink border
• The SPU artifact peak is not added to the Genotypes table
since an artifact is not considered a true allele
• All marker-level and sample-level PQVs (except SQ) turn
gray and maintain their original shape (
) to indicate
that the marker has been edited
• The marker header color changes to gray (pink if selected)
7. Verify the D5S818 marker row is selected in the Genotypes
table, then right-click its
GQ PQV.
8. Click Yes in the dialog box to override the genotype quality and
manually accept the current genotype (11) for the D5S818
marker. The GQ PQV changes to
and the marker header
turns green.
You have completed reviewing the D5S818 marker. You will now
investigate the extra allele present in the FGA marker.
1. Press Ctrl+Minus Sign (–) four times to incrementally zoom
out on all panes of the Samples plot.
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2. Click the red FGA marker header in the red dye pane of
Sample 08 to display the quality assessment details for this
marker.
Note the following:
• The software has detected three alleles in the marker range:
20.2, 24 and 26
• The marker-level
AN PQV is triggered
Note: A
AN PQV indicates that the software detects
either no alleles or more alleles than the Max Expected
Alleles threshold set in the analysis method (in this
example, set to two).
• The marker-level
PHR PQV is triggered
In this example you will assume the extra allele is caused by
pull-up as well.
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3. Left-click the 20.2 peak label, then right-click the label and
select Rename Allele LabelSPU &lt;your initials&gt;.
Note: Note that the SPU custom artifact label you created in
step 5 on page 123 is now displayed in the list of available
labels.
4. In the Reason(s) For Change dialog box, leave the Pull-up text
as shown (recorded in the audit trail), then click OK.
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Note that after editing:
• The SPU artifact label is displayed with a pink border
• The SPU artifact peak is not added to the Genotypes table
since an artifact is not considered a true allele
• All PQVs (except SQ) for the FGA marker turn gray and
maintain their shape (
) to indicate that the marker
has been edited
• The marker header color changes to gray (pink if selected)
5. Verify the row for the FGA marker is selected in the Genotypes
table, then right-click its
GQ PQV.
6. Click Yes in the dialog box to override the genotype quality and
manually accept the current genotype (24, 26) for the FGA
marker.
The next dialog box displays a message indicating that all
marker-level GQ PQVs for sample Sample 08 are now green.
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7. Click No in this Override CGQ dialog box to keep the current
CGQ status for this sample.
You will review this sample further in Chapter 6.
Note that after overriding GQ:
• The GQ PQV changes to
• The marker header turns green
You have now completed reviewing Sample 08.
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Step 5: View Additional Plot Settings
Step 5: View Additional Plot Settings
Additional plot settings are supplied with the GeneMapper&reg; ID-X
Software to assist with performing other functions within the plot
window. Follow the procedures on pages 129 through 132 to review
the elements of these other plot settings.
Select each of the following from the Plot Setting drop-down list:
• Sizing Data – Displays peak detection and sizing information
in a format similar to the ABI PRISM &reg; GeneScan™ software
plots
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Step 5: View Additional Plot Settings
• Check LIZ Size Standard – Displays plots in the same format
as the Check GS500 Macro in the ABI PRISM &reg; Genotyper&reg;
Software templates
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Step 5: View Additional Plot Settings
• Overlay LIZ Dye– Overlays all selected size standard
fragments in one electropherogram pane
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Step 5: View Additional Plot Settings
• Traditional Genotype Plot – Displays plots in a format similar
to the ABI PRISM &reg; Genotyper&reg; Software
After you have finished reviewing each plot setting, you are now
ready to close the Samples plot.
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Step 6: Delete Samples from the Project
Step 6: Delete Samples from the Project
1. Click
(Bring Marked Samples To Top) in the Samples plot
toolbar. The sample (Sample 07) you marked for deletion in
step 8 on page 108 is displayed in the top pane of the Samples
plot.
You can use this feature to verify which samples are marked for
deletion before closing the plot window, since closing the plot
window automatically deletes these samples from the project.
2. Select FileClose Plot Window. A dialog box displays a
message indicating that one sample is marked for deletion.
3. Click Yes in the dialog box to close the Samples plot and return
to the Project window. The software automatically deletes
Sample 07 from the Getting Started project.
Note: From step 4 on page 95, the raw data for Sample 05 is
still displayed in the Project window.
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Step 7: Save the Project
4. Select the Project node in the navigation pane to display the
remaining samples of the Getting Started project in the Samples
table.
Note that Sample 07 is removed from this view. You are now
ready to save your edits to the Getting Started project.
Step 7: Save the Project
Now that you have finished editing the Getting Started project, click
(Save Project) to save all project edits (label edits and
comments) to the GeneMapper&reg; ID-X Software database so they can
be viewed the next time the project is opened.
In Chapter 6, you will review your edits to the Getting Started
project.
First, in Chapter 5 you will use the Profile Comparison tool to help
determine the potential contributors to the negative control with
detected peaks and the mixture sample you just reviewed.
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Chapter 5
Performing Quality Control of
Sample Results
This chapter covers:
Chapter 1
Getting Started
■ Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
■ Understanding the Profile Comparison Tool . . . . . . . . . . . . 137
■ Step 1: Examine Sample Concordance. . . . . . . . . . . . . . . . . 140
Chapter 2
■ Step 2: Perform Sample Comparison and View Results. . . . 141
Setting Up the Software
■ Step 3: Perform Lab Reference Comparison and View Results .
143
■ Step 4: Perform Control/QC Comparison and View Results 144
Chapter 3
Creating a Project,
Analyzing, and Reviewing
Analysis Workflow
Summaries
Chapter 4
Manually Reviewing and
Interpreting Data
Chapter 5
Performing Quality
Control of Sample
Results
Chapter 6
Performing
Peer/Technical Review of
Electronic Data
Chapter 7
Reporting, Exporting and
Printing Results
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Chapter 5 Performing Quality Control of Sample Results
Overview
Overview
About Quality
Control of Sample
Results
Use the Profile Comparison tool to perform quality control of
sample results in a project. Only samples and controls with
or
SQ are included in comparisons (allelic ladder samples are not
included).
The Profile Comparison tool does the following for all samples in a
project:
• Groups samples with 100% concordant profiles
• Compares samples in the project against all other samples in the
project
• Compares samples in the project against lab reference, custom
control, and QC sample profiles stored in the Profile Manager
IMPORTANT! Before you use the Profile Comparison tool to
evaluate the samples in your project, edit allele labels as needed and
ensure that no OL allele labels are present. Samples containing OLlabeled peaks are not considered in comparisons.
In This Chapter
136
In this chapter, you will use the Getting Started project, saved in
Chapter 4, to determine the potential contributors to the Negative
Control and mixture samples observed in Chapter 4 by comparing
the unknown sample profiles in the project against each other and
against the profiles imported into the GeneMapper&reg; ID-X Software
database in Chapter 2.
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Chapter 5 Performing Quality Control of Sample Results
Understanding the Profile Comparison Tool
Understanding the Profile Comparison Tool
Terms You Need
to Know
(
• Reference Profile – The reference profile is the profile against
which another profile is compared to determine the % Match.
The software performs pairwise comparisons to determine the
direction of comparison that yields the higher % Match, then
reports only the direction of comparison with the higher
% Match.
A mixed-source sample is used as a reference profile only when
it is compared to another mixed-source sample.
• Comparison Profile – The comparison profile is compared to
the reference profile to determine the % Match result.
• %-Match – Calculated using the following formula:
# reference profile alleles found in comparison profile
Total # reference profile alleles
)
X
100
Each sample or group (determined in Sample Concordance tab)
is compared to every other individual sample or single-source or
mixed-source group in the project. For a pair of samples or
groups, two comparisons are performed. Each sample/group is
used as a reference, to which the other sample (comparison
sample) is compared. The comparison direction that produces
the highest % Match is reported.
For example:
– Sample 1 is a single-source sample
– Sample 2 is a mixed-source sample
– Sample 1 contains 10 alleles (all of which are found in
Sample 2)
– Sample 2 contains 20 alleles
– When Sample 1 is used as the reference, the
% Match = 100%.
– When Sample 2 is used as the reference, the % Match = 50%.
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Understanding the Profile Comparison Tool
– In this example, the comparison in which Sample 1 is used as
the reference is reported.
Note: Results are reported only when the % Match is greater
than or equal to the user-defined Percent Match Threshold
(range is 50 – 100).
• Single-source groups – Samples with no more than three
alleles in more than one marker in the Genotypes table, and are
100% concordant (all markers and all alleles match).
• Mixed-source groups – Samples with two or more markers
with three or more alleles in the Genotypes table, and are
100% concordant.
• Individual samples – Samples that contain unique profiles.
• Lab Reference and Custom Control Profile – Profiles
imported and stored in the Profile Manager.
Sample
Concordance
The software performs a sample concordance check to group
samples with identical profiles and minimize the number of
comparisons performed on the other tabs of the Profile Comparison
tool.
To perform sample concordance, the software:
• Considers all analyzed samples in the open project with a
(Pass) or
(Check) SQ value, except:
– Allelic Ladder sample types
– Samples that contain OL labels
• Compares each sample against every other sample to determine
100% concordance (all markers and all alleles match).
• Groups 100% concordant profiles in one or more single-source
or mixed-source groups.
Note: The Sample Concordance tab only displays grouped
samples that are 100% concordant. It does not list individual
samples. However, individual samples that meet or exceed the
user-defined Percent Match Threshold are considered in the
Sample Comparison, Lab Reference Comparison, and
Control/QC Comparison tabs.
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Understanding the Profile Comparison Tool
Sample, Lab
Reference,
Custom Control,
and QC
Comparison
To perform comparisons, the software:
• For sample comparisons: Performs a pairwise comparison of all
individual sample, single-source group, and mixed-source
group profiles.
• For lab reference and custom control/QC comparisons:
Compares all individual sample, single-source group profiles,
and mixed-source group profiles to the lab reference or custom
control profiles stored in the Profile Manager (QC comparisons
use custom control profiles).
• Calculates the % Match for each comparison.
• Determines the reference-to-comparison % Match to report.
Note: Only the comparison that yields the highest % Match is
reported. The comparison that yields the lower % Match is not
used or listed in results.
• Displays the % Match results that are greater than or equal to
the user-defined Percent Match Threshold.
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Chapter 5 Performing Quality Control of Sample Results
Step 1: Examine Sample Concordance
Step 1: Examine Sample Concordance
Overview
Examining
Sample
Concordance
In this section, you will use the Profile Comparison tool to check for
concordance among all samples in the Getting Started project.
1. In the Project window, open the Getting Started project (see
step 1 on page 75).
2. Select ToolsProfile Comparison. The Profile Comparison
tool opens to the Sample Concordance tab.
Markers
Alleles
Two single-source groups (Group 1 and Group 2) are listed on
this tab for the Getting Started project.
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Step 2: Perform Sample Comparison and View Results
3. Click
to expand the Samples view for both single-source
groups.
In the Getting Started project, ID_Sample_01 and
ID_Sample_02 (Single Source-Group 1) are 100% concordant,
and ID_Sample_03 and ID_Sample_05 (Single SourceGroup 2) are 100% concordant. All other samples in the project
have unique profiles and are not shown on this tab.
Step 2: Perform Sample Comparison and
View Results
Overview
In this section, you will use the Profile Comparison tool to determine
whether any of the sample profiles in the Getting Started project are
potential contributors to another sample profile in the project.
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Chapter 5 Performing Quality Control of Sample Results
Step 2: Perform Sample Comparison and View Results
Performing
Sample
Comparison
1. Select the Sample Comparison tab.
2. Keep the Percent Match Threshold at 80, then click Compare
Profiles.
Note: The default Percent Match Threshold value is set to 80,
with an accepted range of 50–100 percent.
Viewing the
Results
Review the sample comparison results.
Note: The matching alleles in the reference sample profile
(indicated in bold) and the comparison sample profile are displayed
in blue.
From Chapter 4, you know that ID_Sample_06 in the Getting Started
project is flagged as a potential mixture sample. The sample
comparison results indicate that ID_Sample_08 may be contributing
to the mixed profile of ID_Sample_06 because ID_Sample_08 (the
reference sample) contains 96.7% of the same alleles found in
ID_Sample_06 (the comparison sample).
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Step 3: Perform Lab Reference Comparison and View Results
Step 3: Perform Lab Reference Comparison and
View Results
Overview
Performing Lab
Reference
Comparison
Viewing the
Results
In this section, you will use the Profile Comparison tool to determine
whether any of the lab reference sample profiles stored in the Profile
Manager are potential contributors to sample profiles in the project.
1. Select the Lab Reference Comparison tab.
2. Keep the Percent Match Threshold at 80, then click Compare
Profiles.
Review the lab reference comparison results.
From Chapter 4, we know that the ID_Negative Control sample in
the Getting Started project contains detected, labeled alleles.
The lab reference comparison results indicate that the Analyst A
profile (entered as a lab reference profile in Chapter 2) may be a
contributor to the Negative Control sample, because all of the alleles
detected in the Negative Control sample profile are found in the
Analyst A lab reference profile.
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Chapter 5 Performing Quality Control of Sample Results
Step 4: Perform Control/QC Comparison and View Results
Step 4: Perform Control/QC Comparison and
View Results
Overview
Performing
Control/QC
Comparison
Viewing the
Results
In this section, you will use the Profile Comparison tool to help
perform a blind QC check by comparing the observed profiles for the
custom control and QC samples present in the Getting Started
project to the custom control profiles stored in the Profile Manager
(QC samples use the Custom Control profile type).
1. Select the Control/QC Comparison tab.
2. Keep the Percent Match Threshold at 80, then click Compare
Profiles.
Review the control/QC comparison results.
In the Getting Started project, ID_Sample_04 is run as a QC sample
with profile results expected to match at least one of the custom
control profiles stored in the Profile Manager.
The control/QC comparison results indicate that the QC Sample 01
profile (entered as a custom control profile in the Profile Manager in
Chapter 2) matches a stored custom control profile as expected (all
alleles in ID_Sample_04 are also found in the QC Sample 01 profile).
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Chapter 6
Performing Peer/Technical
Review of Electronic Data
This chapter covers:
Chapter 1
Getting Started
■ Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
■ Step 1: View Samples with Manual Edits and Overrides . . . 146
■ Step 2: View Edits in the Label Edit Viewer . . . . . . . . . . . . 147
Chapter 2
Setting Up the Software
■ Step 3: View Allele Edits and Comments in the Genotypes
Table and Genotypes Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
Chapter 3
Creating a Project,
Analyzing, and Reviewing
Analysis Workflow
Summaries
Chapter 4
Manually Reviewing and
Interpreting Data
Chapter 5
Performing Quality
Control of Sample
Results
Chapter 6
Performing
Peer/Technical Review of
Electronic Data
Chapter 7
Reporting, Exporting and
Printing Results
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Chapter 6 Performing Peer/Technical Review of Electronic Data
Overview
Overview
About Electronic
Peer/Technical
Review
The GeneMapper&reg; ID-X Software provides several data review tools
and features designed to improve the efficiency of electronic
peer/technical review of projects. These features may minimize the
time spent during manual review and eliminate the need to print
electropherograms.
In This Chapter
In this chapter, you will use the Getting Started project results edited
in Chapter 4 to learn how to:
• Use table settings to display only those samples containing
manual edits or overrides
• Visually confirm manual edits using the Label Edit Viewer
• Export the contents of the Label Edit Viewer
• Use table and plot settings to review manual edits
Step 1: View Samples with Manual Edits and
Overrides
Overview
In this section, you will apply several of the default table settings
provided with the software (see Chapter 2) to the Samples table to
display only those samples in the Getting Started project that contain
manual edits or overrides.
Viewing CGQ
Overrides
1. Open the Getting Started project, if not already open (see step 1
on page 75).
2. In the Project window, select View CGQ Overrides from the
Table Setting drop-down list.
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Step 2: View Edits in the Label Edit Viewer
Only those samples in the Getting Started project whose CGQs
were manually overridden in Chapter 4 are shown in the
Samples table:
If a sample is displayed in this list, it means during the previous
interpretation, the analyst manually accepted the sample profile
with or without edits.
Viewing Edited
Samples
In the Project window, select View Edited Samples from the Table
Setting drop-down list.
Only those samples in the Getting Started project that had at least
one allele or artifact label edited in Chapter 4 are shown in the
Samples table:
Note that there is a
in the Sample Edit (SE) column, and the
sample-level PQVs are gray, indicating that peaks within and/or
outside of marker ranges have been edited. This table setting allows
reviewers to focus on only those samples that have been edited. In an
expert system workflow, these may be the only samples that require
second review.
Step 2: View Edits in the Label Edit Viewer
Overview
The Label Edit Viewer contains a list of edits made to the allele and
artifact labels displayed in the sample electropherogram plots of the
Samples plot. In this section, you will use the Label Edit Viewer to
assist in the visual confirmation of manual edits you made to the
Getting Started project in Chapter 4.
You can view the Label Edit Viewer from the Project window or the
Samples plot.
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Step 2: View Edits in the Label Edit Viewer
Viewing Edits
from the Samples
Plot
1. In the Project window, make sure View Edited Samples is
selected from the Table Setting drop-down list.
2. Select the edited sample in the filtered Samples table, then click
(Display Plots).
3. In the Samples plot, select the View Label Edits setting from
the Plot Setting drop-down list. The Samples plot view changes.
This plot setting displays the sample electropherogram plots
above the list of edits shown in the Label Edit Viewer table. In
Chapter 4, you made three label edits to Sample 08 in the
Getting Started project. The Label Edit Viewer displays detailed
information about each of these edits.
Note: The Label Edit Viewer is blank if you have not saved the
project.
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Step 2: View Edits in the Label Edit Viewer
4. To visually confirm the displayed peak labels for Sample 08
against the label edit entries in the Label Edit Viewer, select the
first row in the table. The corresponding edited peak is
highlighted in the electropherogram plot.
Samples plot shows
selected edit
Select row in table
Note: Selecting an edited peak in the electropherogram plot
will also highlight the corresponding edit in the Label Edit
Viewer.
5. Repeat step 4 above for each entry in the Label Edit Viewer.
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Step 2: View Edits in the Label Edit Viewer
6. After you confirm all label edits, manually accept the sample
profile by overriding the CGQ PQV:
a. Right-click the
CGQ in the Samples plot header.
Note: A
CGQ indicates that one or more peaks within
a marker have been edited.
b. Click Yes in the message dialog to override the sample
CGQ. The CGQ PQV changes to
Overridden).
(Manually
Note: Overriding CGQ allows the reviewer to manually
accept the entire profile for a particular sample and also
provides evidence that the sample was visually inspected
by the reviewer.
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Step 2: View Edits in the Label Edit Viewer
7. Select FileClose Plot Window to return to the Project
window.
8. Click
(Save Project) to save your changes to the Getting
Started project.
Viewing Edits
from the Project
Window
1. In the Project window, make sure View Edited Samples is
selected from the Table Setting drop-down list.
2. Select the edited sample in the filtered Samples table, then click
(Label Edit Viewer). The Label Edit Viewer opens in a
separate window.
3. Proceed to the next section if you wish to export the contents of
the Label Edit Viewer. Otherwise, click Close in the Label Edit
Viewer to return to the filtered Samples table.
Exporting the
Label Edit Viewer
from the Project
Window
Note: You can also export the contents of the Label Edit Viewer
from the Samples plot. See “Exporting from the Samples Plot” on
page 168.
1. Display the Label Edit Viewer from the Project window (see
step 2 above).
2. In the Label Edit Viewer, click Export.
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Step 2: View Edits in the Label Edit Viewer
3. In the Export Table dialog, specify a location, name and format
(.txt or .csv) for the exported file, then click Export.
File location
File format
File name
Note: The Files of type selection filters the list of file names
displayed in the navigation pane, it does not determine the
format of the exported file.
4. Click Close in the Label Edit Viewer to return to the filtered
Samples table.
5. Open the exported file with a spreadsheet software that supports
tab-delimited or comma-separated text, such as Microsoft&reg;
Excel&reg;.
6. Print the exported file as needed.
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Step 3: View Allele Edits and Comments in the Genotypes Table and Genotypes Plot
Step 3: View Allele Edits and Comments in the
Genotypes Table and Genotypes Plot
Overview
In this section, you will use the Genotypes table and Genotypes plot
to view the allele edits and comments for the Getting Started project.
Viewing Allele
Calls in the
Genotypes Table
1. In the Project window, select the Project node in the navigation
pane, then select the Genotypes tab.
2. Verify that the View Edited Samples setting is selected from
the Table Setting drop-down list. Only the markers that were
edited in the selected sample (in this example, Sample 08) are
displayed in the Genotypes table.
3. Review the entries in the following table columns:
• Allele Edit (AE) Reason For Change: Displays the last
reason for change entered for an edit that yields an allele
label
• Marker Edit Comment (MEC): Displays the reason for
change entered for an edit that yields an artifact label or
when alleles are deleted
• Marker Edit (ME) flag: Displays
(true) if allele or
artifact labels are edited within a marker size range
Note: You can export the contents of the Genotypes table from
the Project window. This procedure is outlined in “Step 4:
Export Table Data” on page 165.
Viewing Allele
Calls in the
Genotypes Plot
1. In the Project window, Shift-click to select all rows in the
Genotypes table (if not already selected), then click
(Display Plots). The Genotypes plot window opens.
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Step 3: View Allele Edits and Comments in the Genotypes Table and Genotypes Plot
2. In the Genotypes plot, select the Traditional Genotype Plot
setting from the Plot Setting drop-down list. The Genotypes plot
view changes.
This plot setting displays one marker per pane for each of the
markers selected in the Genotypes table. For the Getting Started
project, only the markers for Sample 08 are displayed in the
Genotypes plot.
3. Select FileClose Plot Window to return to the Project
window.
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Chapter 7
Reporting, Exporting and
Printing Results
This chapter covers:
Chapter 1
Getting Started
■ Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156
■ Step 1: Create a Custom Report Setting . . . . . . . . . . . . . . . . 156
■ Step 2: Generate the Report . . . . . . . . . . . . . . . . . . . . . . . . . 160
Chapter 2
■ Step 3: Export the Report . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
Setting Up the Software
■ Step 4: Export Table Data. . . . . . . . . . . . . . . . . . . . . . . . . . . 165
■ Step 5: Print Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
■ Other Export Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168
Chapter 3
Creating a Project,
Analyzing, and Reviewing
Analysis Workflow
Summaries
Chapter 4
Manually Reviewing and
Interpreting Data
Chapter 5
Performing Quality
Control of Sample
Results
Chapter 6
Performing
Peer/Technical Review of
Electronic Data
Chapter
Chapter 77
Reporting, Exporting and
Printing Results
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Chapter 7 Reporting, Exporting and Printing Results
Overview
Overview
In this chapter, you will learn how to generate custom reports, and
export reports and data tables. You will practice these tasks using the
Getting Started project you created using the procedures in Chapter 3
of this guide.
Note: For information on exporting data in a format suitable for
CODIS, see the GeneMapper&reg; ID-X Software Help.
Step 1: Create a Custom Report Setting
Overview
Creating a
Custom Report
Setting
GeneMapper&reg; ID-X Software can generate table-formatted reports
from any combination of the columns in the Samples and Genotypes
tables. You can configure the report with custom columns, save the
report to the project, print it, or export it as tab-delimited or commaseparated text. You can also save the report settings to generate the
same report for other projects.
In this section, you will use the Report Settings Editor to create a
new report setting specifically designed for the Getting Started
project.
1. Launch the software and log in as the Practice User, if not
already logged in (see “Starting the Software and Logging In”
on page 22).
2. Open the Getting Started project, if not already open (see step 1
on page 75).
3. In the Project window, click
(GeneMapper ID-X Manager).
4. In the GeneMapper ID-X Manager, select the Report Settings
tab, then click New. The Report Settings Editor window opens.
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Step 1: Create a Custom Report Setting
5. Complete the top portion of the Report Settings Editor:
a. Enter Getting Started Report &lt;your initials&gt; as the
report Name.
b. Enter a description for the new report setting.
c. Verify that the Practice Security Group is selected from the
drop-down list.
6. Select the Samples table columns to display.
a. In the Sample tab, Ctrl-click to select the following
columns from the Available Columns table.
b. Click
to add these columns to the Selected Columns
table.
Note: Columns you add to the Selected Columns table are
shown in the Preview Table (at the bottom of the Report
Settings Editor).
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Step 1: Create a Custom Report Setting
7. Select the Genotypes table columns to display.
a. In the Genotype tab, Ctrl-click to select the following
columns from the Available Columns table.
b. Click
to add these columns to the Selected Columns
table.
8. Add a custom column to the report. The custom column will
appear as a column of blank, editable cells in the report table.
a. Select the Custom tab, then click Create.
b. Enter the following information, then click OK.
c. In the Custom tab, select the Custom &lt;your initials&gt;
column from the Available Columns table, then click
add this new column to the Selected Columns table.
158
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Chapter 7 Reporting, Exporting and Printing Results
Step 1: Create a Custom Report Setting
9. Adjust the order that the columns appear in the report.
a. In the Selected Columns table, select the Run Date &amp;
Time column.
b. Click
(Move Up) repeatedly until this column is
positioned underneath the Sample Name column.
10. Adjust the column header names to be displayed in the report.
a. In the Display Name column, click the Allele 1 field, then
delete this text and enter Peak 1.
b. Replace Allele 2 with Peak 2.
11. In the Number of Alleles field, verify the number of alleles to
report is set to 2.
12. In the Preview Table, review the column display changes you
just made to the Getting Started Report setting.
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Chapter 7 Reporting, Exporting and Printing Results
Step 2: Generate the Report
13. Click OK to save your settings and close the Report Settings
Editor.
14. Click Done to close the GeneMapper ID-X Manager.
Step 2: Generate the Report
1. In the Project window, make sure the Samples tab is selected,
then select View Unedited Samples from the Table Setting
drop-down list.
1. Shift-click to select the rows Sample 01 through Sample 04 in
the Samples table to report.
2. Click
(Report Manager). A report is displayed in the Report
Manager using the first report setting in the drop-down list.
3. Select the Getting Started Report &lt;your initials&gt; setting you
created from the Report Setting drop-down list.
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Chapter 7 Reporting, Exporting and Printing Results
Step 2: Generate the Report
4. Review the report. Note the following:
• The report contains the columns specified in the report
setting, including the Custom column
• The Allele 1 and Allele 2 columns are reported as Peak 1
and Peak 2
5. To edit a cell in the Custom column, double-click the cell, type
the desired text, then press Enter.
6. Leave the Report Manager window open for the next steps (see
“Step 3: Export the Report” on page 162).
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Chapter 7 Reporting, Exporting and Printing Results
Step 3: Export the Report
Step 3: Export the Report
Overview
Exporting the
Report
You can export the report generated in the Report Manager as a
formatted table. The exported table format depends on the report
setting selected when generating the report. By default, the export
table format reflects the display in the Report Manager window.
However, you can also export in allele table format to list markers in
columns or rows, and to group the called alleles for a marker into one
or more cells, depending on the number of alleles selected to be
displayed.
1. In the Report Manager, select Allele Table from the Report
Setting drop-down list.
Note: You can use this report setting to export genotype data in
a traditional allele table format (see step 6 on page 163).
2. Select FileExport to open the Export Report dialog box:
3. Navigate to the location in which to save the file.
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Chapter 7 Reporting, Exporting and Printing Results
Step 3: Export the Report
4. Enter Export &lt;your initials&gt; as a suffix to the default Getting
Started &lt;your initials&gt;_Allele Table export File name.
Note: The Files of type selection filters the list of file names
displayed in the navigation pane, it does not determine the
format of the exported file.
5. Verify that Tab-delimited text (*.txt) is selected as the export
file format.
Note: This selection separates the alleles with tab-stops, and
allows you to open the exported file using a spreadsheet
application (see step 11 on page 164).
6. Select a format option:
• Apply Selected Report Setting Format (default) –
Exports the report as it is displayed in the Report Manager
(one marker per row)
• Convert to Allele Table by Sample Format – Generates a
list of samples (one sample per row) with column(s) for
each marker that lists the called alleles for the marker
Note: Markers without called alleles are also listed.
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Chapter 7 Reporting, Exporting and Printing Results
Step 3: Export the Report
For heterozygote alleles, you can also choose to:
• Group alleles in one cell – Generates a single column
for each marker and places all alleles for the marker
into one cell (that is, a traditional allele table)
• Separate alleles into individual cells – Generates
multiple columns per marker and places only one
allele per cell
7. Click Export.
Note: If you are exporting an allele table, a dialog box displays
the names of the files created. Click OK.
8. Select FileExit to close the Report Manager.
9. Click Yes in the Save Report dialog, then enter Getting
Started_Allele Table Report &lt;your initials&gt; in the Save
dialog.
10. Click OK to save the Allele Table Report to the Getting Started
project.
11. Navigate to and open the exported Getting Started_Allele
Table Export file in a spreadsheet software (such as Microsoft&reg;
Excel&reg;) or Microsoft&reg; Notepad.
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Chapter 7 Reporting, Exporting and Printing Results
Step 4: Export Table Data
Step 4: Export Table Data
IMPORTANT! When exporting or copying and pasting PQV flags,
include the ME column (from the Genotypes table) and the SE
column (from the Samples table) to indicate whether allele labels
were edited, which may affect individual PQV values.
Exporting
Individual Tables
When you export data from the Samples or Genotypes table
individually, the following are exported in a single table:
• All samples in the project (not selected samples)
• Only the displayed columns from the individual table that you
are viewing
To export individual tables:
1. In the Project window, select ViewSamples, then select the
Samples tab to export the Samples table or the Genotypes tab to
export the Genotypes table.
2. Select View Unedited Samples from the Table Setting dropdown list.
3. Shift-click a column header in the Samples tab (or Genotypes
tab) to sort the table and determine the sample order.
4. Click
(Export Table).
5. In the dialog box, navigate to the location to save the exported
table file.
6. Select the export file format:
• Tab-delimited text (*.txt)
• Comma-delimited values (*.csv)
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Step 4: Export Table Data
7. Enter a name for the exported file.
Note: The Files of type selection filters the list of file names
displayed in the navigation pane, it does not determine the
format of the exported file.
8. Click Export Table.
Exporting
Combined Tables
When you export data from the Samples table and Genotypes table
together, the following are exported in a combined table:
• All samples in the project (not selected samples)
• Only the displayed columns from the Samples table and
Genotypes table
To export combined tables:
1. In the Project window, select View Unedited Samples from the
Table Setting drop-down list.
2. Select FileExport Combined Table.
3. In the dialog box, navigate to the location to save the exported
table file.
4. Select the export file format (*.txt or *.csv).
5. Select a Merge option:
• Allele table by sample
IMPORTANT! This option does not allow you to control
the order of columns in the exported file. Columns are
exported in the order in which they appear in the Samples
and Genotypes tables. To control the order of columns in
the exported file, export from the Report Manager. See
“Step 3: Export the Report” on page 162.
• One line per sample
• One line per marker (default)
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Chapter 7 Reporting, Exporting and Printing Results
Step 5: Print Results
6. Enter a name for the exported file.
7. Click Export.
Note: If you are exporting an allele table, a dialog box displays
the names of the files created. Click OK.
Copying and
Pasting Table
Data
You can copy and paste the content of most tables into a spreadsheet
or text file.
1. In the desired table of the GeneMapper&reg; ID-X Software, select
the cells to copy.
2. To copy the data:
a. Without column headers – Press Ctrl+C.
b. With column headers – Press Ctrl+Shift+C.
3. In the desired location (spreadsheet or text file), select
EditPaste.
Step 5: Print Results
Use the print preview function in the GeneMapper&reg; ID-X Software
to examine data items (reports, tables, plots, sample information, raw
data, and EPT data) on screen before they print.
When you are satisfied with the results, select FilePrint:
Window/Tab
Access From Project Window
By Selecting
Project window – Samples tab
ViewSamples
Project window – Genotypes tab
ViewGenotypes
Project window – Info tab
ViewSample Info
Project window – Raw Data tab
ViewRaw Data
Project window – EPT Data tab
ViewEPT Data
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Chapter 7 Reporting, Exporting and Printing Results
Other Export Options
Window/Tab
Access From Project Window
By Selecting
Samples plot
The Samples tab, then
ViewDisplay Plots
Genotypes plot
The Genotypes tab, then
ViewDisplay Plots
Report Manager
ToolsReport Manager
Size Match Editor
ToolsSize Match Editor
Other Export Options
Exporting from
the Samples Plot
You can export results from the following tables by selecting
FileExport Table in the Samples plot:
Table
Exporting from
the GeneMapper
ID-X Manager
Access From Samples Plot By Selecting
Genotypes table
PlotsTablesGenotypes Table
Label Edit Viewer
PlotsTablesLabel Edit Viewer
Sizing table
PlotsTablesSizing Table
You can export the following data objects stored in the GeneMapper
ID-X Software database by clicking Export... in the GeneMapper
ID-X Manager dialog:
•
•
•
•
•
Projects
Analysis Methods
Table Settings
Plot Settings
Matrices
Note: You can export a matrix file for use in the Data
Collection Software on the ABI PRISM &reg; 310 Genetic Analyzer.
• Size Standards
• Report Settings
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Chapter 7 Reporting, Exporting and Printing Results
Other Export Options
Exporting from
the Panel
Manager
You can export the following data objects stored in the GeneMapper
ID-X Software database by selecting FileExport... in the Panel
Manager window:
•
•
•
•
Exporting from
the Profile
Manager
Panels
Bin Set
All Kits
Marker Stutter
You can export the following data objects stored in the GeneMapper
ID-X Software database by clicking Export in the Profile Manager
dialog:
• Lab Reference profiles
• Custom Control profiles
Note: All of the profiles stored in the Profile Manager will be
exported together in a single file.
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Other Export Options
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GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Index
Symbols
%-Match, definition 137
A
adding, sample files to project 57
AE (Allele Edit) Reason For Change 153
Allele Number (AN) 11
allele, definition 15
allele-calling, definition 16
allelic ladder
definition 15
low-quality 75
quality assessment 3, 10
quality, AS 70
quality, examining 74
quality, status 75
AmpFlSTR&reg; kit, definition 15
AN quality assessment 11
analysis
progress, viewing 67
settings 63
starting 64
status, AS 70
summary 3, 68
analysis method
creating 30
definition 15
analysis requirement check 3
Analysis Requirement Not Met (ARNM) 9
analysis requirements
correcting 66
summary 64
Analysis Requirements Summary (ARS),
reviewing 64
analysis settings, selecting 63
Analysis Summary
about 3, 68
areas 70
features 69
analyzing, project 64, 66
Applied Biosystems
contacting xiii
customer feedback on documentation xii
Information Development department xii
Technical Support xiii
ARNM analysis requirements check 9
assumptions for using this guide ix
audit trail 14
B
BD quality assessment 11
bin
definition 15
viewing 26
BIN quality assessment 11
bin set, definition 15
bold text, when to use ix
Broad Peak (BD) 11
C
CC quality assessment 11
CGQ quality assessment 13
chain-of-custody systems, about 4
CODIS
definition 15
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
171
Index
CODIS (continued)
Web site 15
columns, resizing 24
comparison profile, definition 137
Composite Genotype Quality (CGQ)
allelic ladders 13
samples 13
viewing overrides 146
control
low-quality 86
passing 84
quality, examining 83
quality, status 83
Control Concordance (CC) 11
control quality, AS 70
control/QC comparison
about 139
performing 144
viewing results 144
conventions
bold text ix
for describing menu commands x
IMPORTANTS! x
in this guide ix
italic text ix
Notes x
user attention words x
creating, reports 162
custom control profile, definition 138
custom control, definition 15
customer feedback, on Applied Biosystems
documents xii
D
deleting, sample files from project 133
disclaimer, license ii
documentation, related xi
E
edited samples, viewing 147
172
electronic peer/technical review, about 146
E-signature 14
example data, overview 18
expert system, definition 16
expert system, optimizing and validating 7
exporting
combined tables 166
GeneMapper ID-X Manager results 168
individual tables 165
Label Edit Viewer 151
Panel Manager results 169
Profile Manager results 169
reports 162
results 165
Samples Plot results 168
F
files. See sample files
G
GeneMapper ID-X Manager, exporting 168
Genotype Quality (GQ)
allelic ladders 12
description 12
samples 12
genotype, definition 16
Genotypes Plot window
printing 168
viewing 153
Genotypes table, viewing 153
Getting Started Guide
as a tutorial 18
before starting 17
chapter overviews 18
example data to use 18
how to use 17
required user account 17
GQ quality assessment 12
groups
mixed-source, definition 138
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Index
groups (continued)
single-source, definition 138
H
Help system
accessing xii
exploring 24
MIX quality assessment 13
Mixed Source (MIX)
description 13
examining 99
mixed-source groups, definition 138
MPH quality assessment 11
MSDSs, obtaining xiii
multi-user database, about 5
I
individual samples, definition 138
Information Development department,
contacting xii
italic text, when to use ix
L
lab reference comparison
about 139
performing 143
viewing results 143
lab reference profile, definition 16, 138
Label Edit Viewer
about 147
exporting 151
viewing, from Project window 151
viewing, from Samples plot 148
license disclaimer ii
Low Peak Height (LPH) 11
LPH quality assessment 11
M
manual review tools 4
Marker Spike (SPK) 11
marker-level quality assessments 11
markers, definition 16
Max Peak Height (MPH) 11
ME (Marker Edit) 153
MEC (Marker Edit Comment) 153
menu commands, conventions for
describing x
N
negative control, definition 16
O
Off-scale (OS) 11
OMR quality assessment 13
online Help. See Help system
OS quality assessment 11
Out of Bin Allele (BIN) 11
Outside Marker Range (OMR)
description 13
examining 108
Overlapping Alleles (OVL) 11
OVL quality assessment 11
P
Panel Manager, exporting 169
panels
definition 16
viewing 26
Peak Height Ratio (PHR) 11
percent match, definition 137
PHR quality assessment 11
plot setting
creating 42
defaults 41
reviewing 40
viewing 129
positive control, definition 16
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
173
Index
PQV, definition 16
printing
Genotypes Plot window 168
reports 168
results 167
Samples Plot window 168
Process Quality Value (PQV), definition 16
Profile Comparison tool, about 136, 137
Profile Manager
about 50
exporting 169
profile, definition 16
profiles
adding to database 48
viewing 50
project
adding sample files to 57
analyzing 64, 66
creating 56
definition 16
options 51
saving 134
project options, setting 51
Project window
about 24
viewing edits 151
Q
quality control
about performing 136
overview 4
quality value system
allelic ladder quality assessment 10
analysis requirements checks 9
marker-level quality assessments 11
optimizing 7
overview 7
sample-level quality assessments 13
sizing quality assessment 10
174
R
raw data, viewing 62
reference profile, definition 137
reference project, importing 47
Report Manager, about 5
reports
creating 162
exporting 162
printing 168
results
exporting 165, 168, 169
printing 167
run folder, definition 16
run, definition 16
S
sample
low-quality 89, 90
quality, examining 88
quality, status 88
sample comparison
about 139
performing 142
viewing results 142
sample concordance
about 138
examining 140
sample files
adding to project 57
definition 17
deleting from project 133
location 18
sample information, viewing 60
Sample Off-scale (SOS) 13
sample quality, AS 71
Sample Spike (SSPK)
description 13
examining 92
sample-level quality assessments 13
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Index
Samples Plot window
exporting 168
printing 168
viewing edits 148
samples, viewing edited 147
saving, project 134
security groups 14
single-source groups, definition 138
size standard
defaults 45
definition 17
reviewing 45
Sizing Quality (SQ)
description 10
examining 90, 102
sizing quality assessment 10
software
features 3
overview 2
security 14
setting up 22
starting and logging in 22
terms defined 15
SOS quality assessment 13
SPK quality assessment 11
SSPK quality assessment 13
stutter ratio, definition 17
stutter settings, viewing 26
training, information on xiii
U
user accounts 14
user attention words, described x
T
table setting
creating 37
defaults 36
reviewing 35
tables
copying and pasting data 167
exporting 165, 166
Technical Support, contacting xiii
text conventions ix
traditional manual review, definition 17
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
175
Index
176
GeneMapper&reg; ID-X Software Version 1.0 Getting Started Guide
Worldwide Sales and Support
Applied Biosystems vast distribution and
service network, composed of highly trained
support and applications personnel,
reaches 150 countries on six continents.
For sales office locations and technical support,
please call our local office or refer to our
Web site at www.appliedbiosystems.com.
Applera is committed to providing the
world’s leading technology and information
for life scientists. Applera Corporation
consists of the Applied Biosystems and
Celera Genomics businesses.
Headquarters
850 Lincoln Centre Drive
Foster City, CA 94404 USA
Phone: +1 650.638.5800
Toll Free (In North America): +1 800.345.5224
Fax: +1 650.638.5884
10/2007
www.appliedbiosystems.com
Part Number 4375574 Rev. A
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Automated genotyping software solution
Analysis requirement check
Allelic ladder quality assessment
Analysis Summary
Comprehensive quality value system
Manual review tools
Quality control
Chain-of-custody systems for electronic data
Multi-user database environment
Report Manager

Frequently asked questions

GeneMapper ID-X Software Version 1.0 is an automated genotyping software solution for all human identification (HID) data analysis needs, including forensic casework, databasing, and paternity testing.

The GeneMapper ID-X Software quality value system performs the following checks and assessments: • Analysis requirements checks • Sizing quality assessment • Allelic ladder quality assessment • Marker-level quality assessment • Sample-level quality assessment • Genotype quality assessment

The software provides a quality value system and a set of streamlined data review tools and features for both expert system and traditional manual review workflows. Included in the system are the following features: • Analysis Requirement Check • Allelic Ladder Quality Assessment • Analysis Summary • Comprehensive Quality Value System • Manual Review Tools • Quality Control • Chain-of-Custody Systems for Electronic Data • Multi-User Database Environment • Report Manager