Applied Biosystems Relative Quantitation Analysis Module User

Applied Biosystems Relative Quantitation Analysis Module User
Applied Biosystems™ Relative Quantitation
Analysis Module
USER GUIDE
Publication Number MAN0014820
Revision C.0
For Research Use Only. Not for use in diagnostic procedures.
The information in this guide is subject to change without notice.
DISCLAIMER
TO THE EXTENT ALLOWED BY LAW, LIFE TECHNOLOGIES AND/OR ITS AFFILIATE(S) WILL NOT BE LIABLE FOR SPECIAL, INCIDENTAL, INDIRECT,
PUNITIVE, MULTIPLE, OR CONSEQUENTIAL DAMAGES IN CONNECTION WITH OR ARISING FROM THIS DOCUMENT, INCLUDING YOUR USE OF IT.
REVISION HISTORY: History of Pub. no. MAN0010505
Revision
Date
C.0
June 2016
B.0
March 2016
A.0
September 2015
Description
Outlier Wheel Plot and minor corrections
Software user interface updates
Document release
NOTICE TO PURCHASER: DISCLAIMER OF LICENSE: 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 Life Technologies
Corporation, either expressly, or by estoppel.
Corporate entity: Life Technologies Corporation | Carlsbad, CA 92008 USA | Toll Free in USA 1 800 955 6288
TRADEMARKS: All trademarks are the property of Thermo Fisher Scientific and its subsidiaries unless otherwise specified.
©2016 Thermo Fisher Scientific Inc. All rights reserved.
Contents
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CHAPTER 1 Getting Started . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Getting started . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Analysis workflow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
System requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
Compatible Real-Time PCR System Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
About the software interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Best practices and tips for using the software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
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CHAPTER 2 Manage your projects and experiment data . . . . . . . . . . . . 12
Create a project and add experiment data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Manage projects and experiment data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Share experiments, folders, and projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
About experiment data/files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
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CHAPTER 3 Set up the project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Create or edit an analysis group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Manage samples and targets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
Manage biological groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Configure the analysis settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
Import sample information from design files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
Import target information from AIF files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Define an endogenous control for the analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
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CHAPTER 4 Edit experiment properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Review and edit the plate setups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Apply samples and targets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Specify and assign tasks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Template files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
Apply plate setup information using a template file . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
Applied Biosystems™ Relative Quantitation Analysis Module
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Contents
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CHAPTER 5 Review the raw data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
Review the quality data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
Using the Amplification Plot Histogram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
About the quality data summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
Omit wells from the analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
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CHAPTER 6 Review the analyzed data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
Review the analyzed data and plots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
Box Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
Changing the Box Plot display . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
Correlation Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
RQ Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
Heatmap Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Volcano Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
View and modify the Volcano Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
Melt Curve Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
Omitting wells and samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
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CHAPTER 7 Export the results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
Export the analyzed data from a project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
Export project data as a slide presentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
Export plots for presentation and publication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
Export data for use in other projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
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CHAPTER 8 Screens and plots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
Amplification Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
Box Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
Correlation Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Heatmap Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Melt Curve Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
Multicomponent Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
Outlier Wheel Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
RQ Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
Volcano Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
Well Table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
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Applied Biosystems™ Relative Quantitation Analysis Module
Contents
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CHAPTER 9 Quality flags . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
AMPNC (Amplification in negative control) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
AMPSCORE (Low signal in linear phase) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
BADROX (Bad passive reference signal) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
BLFAIL (Baseline algorithm failed) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
CQCONF (Calculated confidence in the Cq value is low) quality flag . . . . . . . . . . . . . . . . . . . 72
CRTAMPLITUDE (Broad Cq Amplitude) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
CRTNOISE (Cq Noise) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
CTFAIL (Cq algorithm failed) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
DRNMIN (Detection of minimum DRn due to abnormal baseline) quality flag . . . . . . . . . . . 73
EXPFAIL (Exponential algorithm failed) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
HIGHSD (High standard deviation in replicate group) quality flag . . . . . . . . . . . . . . . . . . . . . 74
™
LOWROX (Low ROX Intensity) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
MAXCT (Cq above maximum) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
MPOUTLIER (ΔCq outlier in multiplex experiment) quality flag . . . . . . . . . . . . . . . . . . . . . . . 75
MTP (Melt curve analysis shows more than one peak) quality flag . . . . . . . . . . . . . . . . . . . . 75
NOAMP (No amplification) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
NOISE (Noise higher than others in plate) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
NOSAMPLE (No sample assigned to well) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
NOSIGNAL (No signal in well) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
OFFSCALE (Fluorescence is offscale) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
OUTLIERRG (Outlier in replicate group) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
PRFDROP (Passive reference signal changes significantly near the Cq/Ct) quality flag . . 79
PRFLOW (Average passive reference signal is below the threshold) quality flag . . . . . . . . 80
SPIKE (Noise spikes) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
THOLDFAIL (Thresholding algorithm failed) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
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APPENDIX A Documentation and support . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
Customer and technical support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
Limited product warranty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
Applied Biosystems™ Relative Quantitation Analysis Module
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Getting Started
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Getting started . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Analysis workflow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
System requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
Compatible Real-Time PCR System Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
About the software interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Best practices and tips for using the software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
The Applied Biosystems™ Analysis Software is a secure web application for analysis
of data generated on Thermo Fisher Scientific real-time PCR instruments. The
software provides project-based analysis of real-time and end-point data for a variety
of quantitative and qualitative PCR applications.
Getting started
The Applied Biosystems™ Analysis Software supports both the Comparative CT
(ΔΔCT) and Relative Standard Curve methods of relative quantitation of gene
expression.
Comparative CT (ΔΔCT) method
The comparative CT (ΔΔCT) method is used to determine the relative target quantity
in samples. With the comparative CT method, the Applied Biosystems™ Analysis
Software measures amplification of the target and of the endogenous control in
samples and in a reference sample. Measurements are normalized using the
endogenous control. The software determines the relative quantity of target in each
sample by comparing normalized target quantity in each sample to normalized target
quantity in the reference sample.
Comparative CT experiments are commonly used to:
• Compare expression levels of a gene in different tissues.
• Compare expression levels of a gene in a treated sample vs. an untreated sample.
• Compare expression levels of wild-type alleles vs. mutated alleles.
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Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 1 Getting Started
Getting started
1
The following components are required to perform a comparative Cq analysis and
must be present on all experiments added to the project:
• Sample – The sample in which the quantity of the target is unknown.
• Reference sample – The sample used as the basis for relative quantitation results.
For example, in a project of drug effects on gene expression, an untreated control
would be an appropriate reference sample. Also called calibrator.
• Endogenous control – A target or gene that should be expressed at similar levels
in all samples you are testing. The endogenous control is used to normalize
fluorescence signals for the target you are quantifying. Housekeeping genes can
be used as endogenous controls.
• Replicates – The total number of identical reactions containing identical samples,
components, and volumes.
• Negative controls – Wells that contain water or buffer instead of sample
template. No amplification of the target should occur in negative control wells.
Relative standard curve method
The Relative Standard Curve method is used to determine relative target quantity in
samples using a standard curve as the basis for comparison. With the relative
standard curve method, the instrument measures the amplification of the target and
endogenous control within unknown samples, a reference sample, and in a standard
dilution series. During the analysis, the measurements are normalized using the
endogenous control, then data from the standard dilution series are used to generate
the standard curve. Using the standard curve, the software interpolates the quantities
of the target and endogenous control in the unknown and reference samples. For each
sample, the target quantity is normalized by the endogenous control quantity
(quantity of target/quantity of endogenous control). The normalized quotient from
each sample is divided by the quotient from the reference sample to obtain the
relative quantification (fold change). The software determines the relative quantity of
target in each sample by comparing target quantity in each sample to target quantity
in the reference sample.
Relative Standard Curve experiments are commonly used to:
• Compare expression levels of a gene in different tissues.
• Compare expression levels of a gene in a treated sample and an untreated
sample.
• Compare expression levels of wild-type alleles and mutated alleles.
• Analyze the gene expression changes over time under specific treatment
conditions.
The following components are required to perform a relative standard curve analysis
and must be present on all experiments added to the project:
• Sample – The tissue group that you are testing for a target gene.
• Reference sample (also called a calibrator) – The sample used as the basis for
relative quantification results. For example, in a study of drug effects on gene
expression, an untreated control is an appropriate reference sample.
• Standard – A sample that contains known quantities of the target; used in
quantification experiments to generate standard curves.
• Standard dilution series – A set of standards containing a range of known
quantities. The standard dilution series is prepared by serially diluting standards.
Applied Biosystems™ Relative Quantitation Analysis Module
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Chapter 1 Getting Started
Analysis workflow
• Endogenous control – A gene that is used to normalize template input
differences, and sample-to-sample or run-to-run variation.
• Replicates – The total number of identical reactions containing identical
components and identical volumes.
• Negative Controls – Wells that contain water or buffer instead of sample
template. No amplification of the target should occur in the negative control
wells.
Analysis workflow
The following figure shows the general workflow for analyzing projects using the
Applied Biosystems™ Analysis Software.
START
q
Create a project
q
Import and add experiment data
q
(Optional) Add and define analysis settings, samples, and targets
q
Review/edit the sample, target, and task configurations of the added
experiments
q
Review the quality data and adjust the analysis settings if necessary
q
Review the results of the analysis and further refine the settings
q
Publish the project data
q
FINISH
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Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 1 Getting Started
System requirements
1
System requirements
The following table summarizes the system requirements for the user environment.
Applied Biosystems™ Analysis Software performance may vary based on your system
configuration.
Category
Web Browser
Requirement
• Apple™ Safari™ 8 Browser
• Google™ Chrome™ Browser Version 21 or later
• Microsoft™ Internet Explorer™ Browser Version 10 or later
• Mozilla™ Firefox™ Browser Version v10.0.12 or later
Operating
System
Network
Connectivity
• Windows™ XP, Vista, 7, or 8
• Macintosh™ OS 8 or later
An internet connection capable of 300kbps/300kbps (upload/download)
or better.
If your network employs a firewall that restricts outbound traffic, it
must be configured to allow outbound access to
apps.lifetechnologies.com on HTTPS-443.
Applied Biosystems™ Relative Quantitation Analysis Module
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Chapter 1 Getting Started
Compatible Real-Time PCR System Data
Compatible Real-Time PCR System Data
The Applied Biosystems™ Analysis Software can import and analyze data generated
by any of the supported instruments listed in the following table. The software
versions listed in the table represent only those tested for use with the Applied
Biosystems™ Software. Data generated by versions other than those listed can be
imported and analyzed by the software, but are not supported by Thermo Fisher
Scientific.
IMPORTANT! The Applied Biosystems™ Analysis Software can import and analyze
data from unsupported versions of the instrument software; however, we cannot
guarantee the performance of the software or provide technical support for the
analyses.
Real-Time PCR System
Supported software
version(s)
Applied Biosystems™ 7900 HT Fast Real-Time PCR
System
v2.4 or later
™
Applied Biosystems 7500 and 7500 Fast RealTime PCR System
™
™
Applied Biosystems StepOne and StepOnePlus
Real-Time PCR System
v2.0.5 or later
™
Applied Biosystems™ QuantStudio™ 12K Flex RealTime PCR System
Applied Biosystems™ QuantStudio™ 5 Real-Time
PCR System
Applied Biosystems™ QuantStudio™ 6 Flex RealTime PCR System
Applied Biosystems™ QuantStudio™ 7 Flex RealTime PCR System
10
.sds
v1.4.1 or later
Applied Biosystems™ ViiA™ 7 Real-Time PCR
System
Applied Biosystems™ QuantStudio™ 3 Real-Time
PCR System
File
extension
v2.0.1, v2.1, or later
v1.1 or later
v1.1.1 or later
.eds
v1.0 or later
v1.0 or later
Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 1 Getting Started
About the software interface
1
About the software interface
The Applied Biosystems™ Software features a simple interface for analyzing
experiment data and includes the following buttons/icons in many of the screens and
plots:
4
5
6
7
8
9
3
10
2
12
13
1
11
1
2
3
4
5
Analysis Modules – Click to analyze the current project
using the selected module.
(Data Manager) – Click to view the Data Manager,
which can be used to view, add, or remove data from the
current project.
(Project Manager) – Click to view the Project
Manager, which can be used to modify the current project
or open another.
(Account Management Menu) – Click to manage your
application licenses or storage.
Project name – The name of the current project.
Note: Click
to close the project.
Project tabs – Click to view the settings, data, or plot(s)
for the current project.
7
(Notifications) – Click to view important information
and notifications for the current project. The digit within
the icon indicates the number of messages.
6
(Help) – Click to access help topics relevant to the
current settings, data, or plot that you are viewing.
9
(Profile Menu) – Click to change your profile settings
or to log out of the Applied Biosystems™ Software.
10 Analyze – Click to analyze the project after you have
made a change.
11
(Zoom) – Click to magnify the related table or plot to
fill the screen.
8
Note: Once expanded, click
(Close) to collapse the
plot or table to its original size.
12 Settings – Click to edit the analysis settings for the
project.
13 Actions – Click to select from a list of actions that pertain
to the related table or plot.
Best practices and tips for using the software
The Applied Biosystems™ Analysis Software provides a variety of useful user
interface elements that will enable you to better organize your data for analysis and
presentation. This topic describes the essentials of the user interface and how to best
use them.
Perform the following actions to help ensure optimal performance of the Applied
Biosystems™ Software:
• Refresh your browser regularly
• Clear your browser cache
Applied Biosystems™ Relative Quantitation Analysis Module
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Manage your projects and
experiment data
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■
■
Create a project and add experiment data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Manage projects and experiment data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Share experiments, folders, and projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
About experiment data/files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Use the Data Manager screen to add and remove experiments to and from your
project. The screen displays all experiments associated with the current project. You
can also use the Data Manager to upload new .eds and .sds files or view the details of
individual experiments already added to the project.
Create a project and add experiment data
1. Click
(Manage Projects) to view the Dashboard.
2. Create the project:
New Project.
a. Click
b. In the Create Project dialog box, enter a name for the project, select the
folder within which you want to place the project, then click OK.
Note: The project name cannot exceed 50 characters and cannot include any
of the following characters: / \ < > * ? " | : ; & % $ @ ^ ( ) !
12
Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 2 Manage your projects and experiment data
Manage projects and experiment data
2
3. From the Manage Data screen, add any additional experiment data to the project.
To import
experiment data
stored on…
Action
1. Click Import from local.
2. From the Open dialog box, select one or more experiment
files (.sds or .eds), then click Open.
Your computer
Note: Ctrl- or Shift-click to select multiple files.
Wait for the Applied Biosystems™ Software to upload the
selected data.
3. Click Close prompted that the import is complete.
1. Click Import from Thermo Fisher Cloud.
Thermo Fisher
Cloud
2. Select one or more experiment files (.sds or .eds) from
the table, then click Add.
3. When you are done adding files to the queue, click OK.
4. Click Close prompted that the import is complete.
4. Repeat step 3 until your project contains all of the desired experiment data.
5. Click the appropriate analysis module on the left side of the screen to begin the
analysis.
Manage projects and experiment data
Use the Manage Data screen to add and remove experiment data to/from your project:
• Add experiment data to your project:
a. While viewing your project, click
side of the screen.
(Manage Data) from the bar on the left
b. From the Manage Data screen, add any additional experiment data to the
project.
To import
experiment data
stored on…
Action
1. Click Import from local.
Your computer
2. From the Open dialog box, select one or more
experiment files (.sds or .eds), then click Open.
Note: Ctrl- or Shift-click to select multiple files.
1. Click Import from Thermo Fisher Cloud.
Thermo Fisher
Cloud
2. Select one or more experiment files (.sds or .eds)
from the table, then click Add.
3. When you are done adding files to the queue, click OK.
Applied Biosystems™ Relative Quantitation Analysis Module
13
2
Chapter 2 Manage your projects and experiment data
Share experiments, folders, and projects
c. Wait for the Applied Biosystems™ Software to import the selected data.
When you are prompted that the upload is complete, click Close.
• Delete projects, experiments, or folders:
a. Select the experiments from the Files in this project table that you want to
remove.
b. From the Manage Data screen, select Actions4Delete.
c. When prompted, click OK to remove the experiment(s) from your project.
Note: Click the appropriate analysis module on the left side of the screen to return to
the analysis.
Share experiments, folders, and projects
The Applied Biosystems™ Analysis Software allows you to share any data
(experiments, folders, and projects) with other users that have access to the software.
Sharing data with other users grants them different access to the data depending on
the type of object shared:
• Projects – Sharing a project with other users grants them read/write access to the
unlocked project.
IMPORTANT! A project is locked (preventing access) when it is open (in use) by
any user with shared access to the project. For example, User A shares a project
with two colleagues (User B and User C), User B opens the project and begins
data analysis (the project is locked and unavailable to Users A and C) until User B
closes the project at which time it is available again to all three users.
• Experiments – Sharing experiment files with other users grants them full access
to the data, allowing them to import the data to their own projects or download
the experiment data file.
• Folders – Sharing a folder with another user grants access to the contents of the
folder (projects, experiments, and subfolders).
To share projects, experiments, and subfolders with another user:
• Share an experiment, folder, or project:
(Home), then click
All Files to view your data.
a. Click
b. From the Home Folder screen, select the check box to the left of the object
(display
(project, experiment, or folder) that you want to share, then click
details).
14
Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 2 Manage your projects and experiment data
Share experiments, folders, and projects
2
c. Enter the email address of the user with whom you want to share the
selected object, then click .
The user is notified via email that you have shared with them and the shared item
will appear in their Home Folder.
IMPORTANT! To share multiple files:
1. Select the desired objects (projects, experiments, and subfolders) from the
Home Folder screen, then click Actions4Share.
2. In the Share Files dialog box, enter the email address of the user with whom
you want to share the selected objects, then click Share.
• Un-share a file, folder, or project:
(Home), then click
a. Click
All Files to view your data.
b. Select the shared object, then click the display details
icon.
c. In the details pane, select the Shared With tab, then click un-share adjacent
to the email address of the user from which you want to remove sharing
privileges.
The selected users are notified via email that you are no longer sharing the
specified file with them and the shared file(s) will no longer appear in their
Home Folder.
Applied Biosystems™ Relative Quantitation Analysis Module
15
2
Chapter 2 Manage your projects and experiment data
About experiment data/files
About experiment data/files
The Applied Biosystems™ Analysis Software can import and analyze experiment files
(.eds and .sds) that are generated by a variety of Thermo Fisher Scientific real-time
qPCR instruments. Every consumable run on a Thermo Fisher Scientific real-time
qPCR instrument requires the creation of one or more experiment files that store the
associated data. Each experiment file is a virtual representation of a specific
consumable (plate, array, or chip) that contains data for all aspects of the qPCR
experiment.
Experiment files contain the following information:
• Target information and arrangement on the plate
• Sample information and arrangement on the plate
• Method parameters for the run
File compatibility
The Applied Biosystems™ Software can import data the following experiment file
formats generated by Applied Biosystems™ real-time qPCR instruments:
IMPORTANT! The Applied Biosystems™ Analysis Software can import and analyze
data from unsupported versions of the instrument software; however, we cannot
guarantee the performance of the software or provide technical support for the
analyses.
Real-Time PCR System
Supported software
version(s)
Applied Biosystems™ 7900 HT Fast Real-Time PCR
System
v2.4 or later
™
Applied Biosystems 7500 and 7500 Fast RealTime PCR System
Applied Biosystems™ StepOne™ and StepOnePlus™
Real-Time PCR System
Applied Biosystems™ ViiA™ 7 Real-Time PCR
System
Applied Biosystems™ QuantStudio™ 12K Flex RealTime PCR System
Applied Biosystems™ QuantStudio™ 3 Real-Time
PCR System
Applied Biosystems™ QuantStudio™ 5 Real-Time
PCR System
Applied Biosystems™ QuantStudio™ 6 Flex RealTime PCR System
Applied Biosystems™ QuantStudio™ 7 Flex RealTime PCR System
16
File
extension
.sds
v1.4.1 or later
v2.0.5 or later
v2.0.1, v2.1, or later
v1.1 or later
v1.1.1 or later
.eds
v1.0 or later
v1.0 or later
Applied Biosystems™ Relative Quantitation Analysis Module
3
Set up the project
■
■
■
■
■
■
■
Create or edit an analysis group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Manage samples and targets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
Manage biological groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Configure the analysis settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
Import sample information from design files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
Import target information from AIF files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Define an endogenous control for the analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
After importing one or more experiments (.eds or .sds files) into your HRM project,
use the Overview screen to set up the project.
Create or edit an analysis group
When a project is created, the Applied Biosystems™ Analysis Software generates the
default analysis group from the analysis settings of the experiments added to the
project. If desired, you can create additional analysis groups to explore different
analysis setting configurations (for example, manual versus automatic thresholding,
stringent versus relaxed quality thresholds, etc).
1. From the Analysis Groups table in the Overview screen, do one of the following:
• Select Actions4Add to create a new analysis group.
• Select an existing group, then select Actions4Edit Analysis Settings. Go to
step 4.
2. From the Analysis Settings dialog box, enter the following information, then
click Next.
• Group Name – Enter a name for the analysis group (up to 50 characters).
• (Optional) Description – Enter a description for the analysis group (up to
256 characters).
• Samples or Experiments – Select the option to determine the basis by which
the Applied Biosystems™ Software will apply the analysis group.
For example, by selecting "Sample", the software allows you to apply the
analysis group to a subset of the samples within the project. Conversely, by
selecting "Experiment", the software allows you to apply the analysis group
to only some of the experiments or reaction plates added to the project.
3. From the Analysis Group: Content dialog box, select the samples or experiments
to which the analysis group will apply, then click Next.
Applied Biosystems™ Relative Quantitation Analysis Module
17
3
Chapter 3 Set up the project
Create or edit an analysis group
4. From the Analysis Group: Analysis Setting dialog box, modify the analysis
settings as desired.
Group
Settings
Endogenous Controls Select the method that the Applied Biosystems™ Software will use to normalize the data and
identify the endogenous control (if used):
1. Select an option for specifying the endogenous control:
• Use specific endogenous control – Select to specify one or more endogenous
controls from the list of targets.
• Use global normalization – Select to allow the Applied Biosystems™ Software to
algorithmically normalize the C T scores to calculate relative expression.
2. If you chose to use specific endogenous controls, select one or more targets from the
list to use as the endogenous control(s) for the selected analysis group.
RQ Settings
• Analysis Type – Multiplex or Singleplex. In multiplex analysis, the target(s) of interest
and the endogenous control are in the same well; for singleplex analysis, the target(s) of
interest and the endogenous controls are in different wells. For multiplex analysis, ∆CT
(or ∆CRT) is calculated at the well level.
• Reference Sample and Reference Biological Group – Select the sample and/or
biological group to use as the reference. The samples or other biological groups are
compared to the reference to determine relative quantities of target.
• Confidence level (exclude results below this level) – Select to calculate the RQ
minimum and maximum values for the selected confidence level. Select the confidence
level to use. (RQ min/max values are derived using standard error.)
• Limit by standard deviations – Select to calculate the RQ minimum and maximum
values for the selected number of standard deviations. Select the number of standard
deviations to use. (RQ min/max values are derived using standard deviation.)
• Benjamin-Hochberg false discovery rate for p-values – Select to use the BenjaminHochberg statistical method to adjust the p-values for the analysis.
• Maximum allowed CT – Enter the maximum allowed CT (or CRT) value. Any value greater
than this is rounded down to this value.
• Include maximum CT values in calculation – Select whether to include the rounded
values in any calculations.
Efficiency
For targets with amplification efficiency other than 100%, click in the Efficiency (%) column,
then enter a percentage value between 1% and 150% to correct the amplification efficiency.
Cq Settings
Select the method (CT or CRT) that the Applied Biosystems™ Software will use to compute the
Cq (CT) values for the analysis group:
• CT method – Define whether each target will use automatic thresholding and/or
baselining. If you are using manual settings, enter the manual threshold and baseline
values for the appropriate targets.
• CRT method – Specify the cycle number that the software will use as the minimum
parameter in defining the relative threshold for the CRT calculation.
Note: If you are using a global, standardized set of CT settings for baselining and
thresholding, you can apply the global settings using a CT Settings file. To generate the file,
click Export CT Settings after you set the Cq settings as desired. The exported file can then
be used to set the settings for subsequent projects by importing it.
18
Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 3 Set up the project
Create or edit an analysis group
Group
Flag Settings
3
Settings
Specify the quality measures that the Applied Biosystems™ Software will compute during the
analysis.
1. In the Use column, select the check boxes for flags you want to apply during analysis.
2. If an attribute, condition, and value are listed for a flag, you can specify the setting for
applying the flag.
For example, with the default setting for the no amplification flag (NOAMP), wells are
flagged if the amplification algorithm result is less than 0.1.
Note: If you choose to adjust the setting for applying a flag, make minor adjustments as
you evaluate the appropriate setting.
3. In the Reject column, select the check boxes if you want the software to reject wells
with the flag. Rejected wells are not considered for data analysis.
Inter-plate Calibrator Specify whether the Applied Biosystems™ Software will perform the analysis using an interplate calibrator.
Settings
An IPC is a positive qPCR control, template, and assay that can be added to qPCR
experiments in a project to provide a method for normalization. When the experiments are
added for a collective analysis, a comparison of inter-plate calibrator performance can be
used to account for minor variations in instrument performance.
1. Identify the target and sample combination to use as the inter-plate calibrator.
IMPORTANT! The inter-plate calibrator must be present on the reaction plates of all
experiments added to your project. Include at least three technical replicates on each
reaction plate to ensure optimal performance of the calibrator.
2. Click Add Inter-plate Calibrator Settings, then double-click the table cells in the Target
and Sample columns to select the inter-plate calibrator target and sample.
3. Repeat the previous step to add additional inter-plate calibrators to the analysis
settings.
4. If desired, select Allow calculation of delta Cq across all plates in the analysis group to
activate cross-plate calculation of ∆Cq values.
Note: To remove an inter-plate calibrator setting, select the appropriate row from the table,
click Delete Inter-plate Calibrator Settings, then click OK.
Applied Biosystems™ Relative Quantitation Analysis Module
19
3
Chapter 3 Set up the project
Manage samples and targets
Group
SC Settings
Settings
If you are using a relative standard curve to perform relative quantitation, specify standard
curve settings that the Applied Biosystems™ Software will use to perform the analysis .
The Relative Standard Curve is generated from a standard dilution series that is either
present on the reaction plate with the unknowns or run separately on another plate. In both
cases, data from the standards are normalized to the amplification of an endogenous control
and then used to generate the standard curve for quantitation. To construct the curve, you
must use the SC Settings to specify the location of the standards and select the curve from
those detected by the software.
1. Select the location of the standard curve:
• On Plate Standard Curve – Select if the standard curve reactions are located on the
same reaction plate as the unknowns.
If you want to use an on-plate standard curve to analyze other experiments,
click Export and save the file.
• External Standard Curves – Select if the standard curve reactions are located on a
different reaction plate that was run separately.
IMPORTANT! Before you can import an external standard curve, you must export it
from the related experiment.
2. (External curve only) Click Import, then select the experiment from which you want to
import the standard curve data.
3. Select the standard curve that you want to use from the Standard Curves table.
Note: To remove an external standard curve from an analysis, select the curve from the
Standard Curves table, click Delete, then click OK.
5. When done modifying the analysis settings, click Finish.
6. Click Analyze to reanalyze your project.
Manage samples and targets
The Applied Biosystems™ Analysis Software populates the Overview screen with the
samples and targets present in the experiments added to the project. If necessary, you
can add, edit, or remove the samples and targets as needed before the analysis.
• Create a new sample or target:
a. From the Samples or Targets table in the Overview screen,
click Actions4Add.
b. In the New Sample/Target dialog box, enter a name for the new sample or
target (up to 256 characters), then edit the properties of the new
sample/target.
c. Click OK.
• Update an existing sample or target by editing the entry directly in the table.
Note: Alternately, select a sample or target from the table, then
select Actions4Assign/Update.
20
Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 3 Set up the project
Manage biological groups
3
• Delete a sample or target:
a. From the Samples or Targets table in the Overview screen, select the sample
or target of interest, then click Actions4Delete.
b. In the confirmation dialog box, click OK to delete the sample or target.
Manage biological groups
If your project uses biological replicates, assign biological replicate groups to the
samples to associate the data. The use of biological groups is optional and applicable
when an experiment uses reactions with identical components and volumes to
evaluate separate samples of the same biological source (for example, samples from
three different mice of the same strain, or separate extractions of the same cell line or
tissue sample). When an experiment uses biological replicate groups in a project, the
results are calculated by combining the results of the separate biological samples and
treating this collection as a single population (that is, as one sample).
You can use the Applied Biosystems™ Analysis Software to do the following:
• Create a new biological group:
a. From the Bio Groups table in the Overview screen, select Actions4Add.
b. In the Add New Biological Group dialog box, enter a name for the new
group (up to 256 characters), then click OK.
c. Edit the properties of the biological group directly in the BioGroups table,
then click OK.
– (Optional) Select a color from the drop-down menu. (The color is shown
in the box plot.)
– Enter up to a 72-character description of the biological group.
• Update an existing biological group by editing the group directly in the table.
Note: Alternately, select a biological group from the table, then
select Actions4Update.
• Assign samples to biological groups:
a. From the Samples table in the Overview screen, select one or more samples
from the list, then select Actions4Assign.
b. In the Update Sample dialog box, select the desired biological group, then
click OK.
• Delete a biological group:
a. From the Bio Groups table in the Overview screen, select the biological
group of interest, then select Actions4Delete.
b. In the confirmation dialog box, click OK to delete the group.
Applied Biosystems™ Relative Quantitation Analysis Module
21
3
Chapter 3 Set up the project
Configure the analysis settings
Configure the analysis settings
The Applied Biosystems™ Analysis Software applies analysis settings through the use
of analysis groups. You can either edit the analysis settings for the default analysis
group or create additional groups to capture changes to the settings for later
comparison.
See “Create or edit an analysis group“ on page 17 for more information.
Import sample information from design files
For convenience, the Applied Biosystems™ Software can import sample information
directly from design files exported from projects or created using a text editor or
spreadsheet application. Design files are formatted as either tab-delimited (.txt) or as
comma-separated (.csv) text. The following figure illustrates the structure of the
exported file.
1
2
A
sample name
group
B
Adipose1
Adipose
C
Adipose2
Adipose
D
Bladder1
Bladder
E
Bladder2
Bladder
3
4
5
6
7
8
Use the following guidelines when editing the file:
• Row A – The first row of the file must contain the sample name and group
column headers.
• Column 1 (sample name) – For each row, enter a name for a single sample (up to
100-characters).
• Column 2 (group) – For each row, enter the name of the biological group to
which you want to assign the sample.
Note: If you are not using biological groups, leave the second column blank. The
Applied Biosystems™ Software does not import blank entries.
• If the samples included in the design file are present in other experiments
included in the project, the names in the file must match those in the other
experiments exactly (including case) in order for the software to associate the
data.
You can perform the following related actions from the Overview screen:
• Create a design file:
If you have already added an experiment to your project, you can download a
template file that you can use as a starting point to create your own template files.
a. From the Samples table in the Overview screen, click Actions4Export
Design File.
22
Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 3 Set up the project
Import target information from AIF files
3
b. In the Export Sample Settings dialog box, select the format for the exported
file (.txt or .csv), then click OK.
c. Using a text editor or spreadsheet application, open the sample design file
and edit it as needed.
• Import a design file:
a. From the Samples table in the Overview screen, click Actions4Import
Design File.
b. Locate the sample design file with the sample information, then click Open.
If the import is successful, the sample(s) are populated to the samples in the table. If a
sample of the same name is already present in the project, it is overwritten with the
information from the sample design file.
Note: Sample name matching is not case-sensitive. For instance, if the sample in the
project is "fly", then both "fly" and "Fly" in the sample design file will match.
Import target information from AIF files
For convenience, the Applied Biosystems™ Software can import target information
directly from assay information files (.aif), which are supplied with assays
manufactured by Thermo Fisher Scientific. AIF are tab-delimited data files provided
on a CD shipped with each assay order. The file name includes the number from the
barcode on the plate.
1. From the Targets table in the Overview screen, click Actions4Import AIF File.
2. Locate the .aif file with the target information, then click Open.
If the import is successful, the target is populated to the appropriate table. If a target
of the same target name is already present in the project, it is overwritten with the
information from the AIF.
Note: Assay/target name matching is not case sensitive.
Define an endogenous control for the analysis
In the Applied Biosystems™ Analysis Software, the endogenous control is assigned
within, and is specific to, each analysis group.
1. From the Analysis Groups table in the Overview screen, select an existing group,
then select Actions4Edit Analysis Settings.
2. Click Endogenous Controls to view the settings.
Applied Biosystems™ Relative Quantitation Analysis Module
23
3
Chapter 3 Set up the project
Define an endogenous control for the analysis
3. Select an option for specifying the endogenous control:
• Use specific endogenous control – Select to specify a specific endogenous
control from the list of targets.
• Use global normalization – Select to allow the Applied Biosystems™
Software to algorithmically normalize the CT scores to calculate relative
expression.
4. If you chose to use a specific endogenous control, select one or more targets from
the list to use as the control(s) for the selected analysis group.
5. Click Finish.
24
Applied Biosystems™ Relative Quantitation Analysis Module
4
Edit experiment properties
■
■
■
■
■
Review and edit the plate setups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Apply samples and targets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Specify and assign tasks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Template files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
Apply plate setup information using a template file . . . . . . . . . . . . . . . . . . . . . . . 29
After populating your project with samples, targets, and controls, use the Plate Setup
screen to make changes to the plate setups of the experiments added to your project.
The editor can be used to edit sample, target, task, and control assignments to correct
missing or incorrect settings.
Review and edit the plate setups
After configuring your project with all necessary samples, targets, and biological
groups, use the Plate Setup screen to review the experiments for problems that can
prevent the analysis of the project. The Applied Biosystems™ Analysis Software
displays plate configuration errors that can prohibit analysis in the margin beneath
each image of the related experiment. Before you can analyze your project, you must
use the Plate Setup screen to address them.
To review the plate setup information for your project:
1. Select Plate Setup to display Plate Setup screen.
2. From the Plate Setup screen, review the experiment records for errors.
3. If errors are present, click the experiment record of interest and address the
problem that is preventing the analysis of the file.
Note: The software displays plate configuration problems that will prevent
analysis of an experiment beneath the image of the related plate.
Applied Biosystems™ Relative Quantitation Analysis Module
25
4
Chapter 4 Edit experiment properties
Apply samples and targets
Apply samples and targets
If the sample or target assignments of one or more of your experiments contain errors
or are missing, you can use the Applied Biosystems™ Analysis Software to correct the
problem prior to analysis.
Note: When reviewing a plate layout, click Actions4Clear Well Setup to remove the
well information (sample, task, and target assignments) from the selected wells in the
plate grid.
1. From the Plate Setup screen, select the experiment that you want to modify.
2. (Optional) From the Edit Plate screen, click View , then select Target and
Sample to color the plate setup according to the element that you intend to
modify.
3. Select the wells of the plate layout to which you want to apply the target or
sample.
4. When the wells are selected, click the appropriate field to the right of the plate
grid, then select the appropriate item from the list.
Note: If you have not yet created a sample or target, enter the name in the
appropriate field and press Enter to create the new sample or target.
5. Once you are finished making changes to the plate layout, click Analyze to
reanalyze your project.
26
Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 4 Edit experiment properties
Specify and assign tasks
4
Specify and assign tasks
If the task assignments of one or more of your experiments contain errors or are
missing, you can use the Applied Biosystems™ Analysis Software to correct the
problem prior to analysis.
Note: When reviewing a plate layout, click Actions4Clear Well Setup to remove the
well information (sample, task, and target assignments) from the selected wells in the
plate grid.
1. From the Plate Setup screen, select the experiment record that you want to
modify.
2. From the Edit Plate screen, click View
setup according to task assignment.
, then select Task to color the plate
3. Select the wells of the plate layout to which you want to apply a task.
4. When the wells are selected, click the Task menu, then select the appropriate task
from the list.
Available tasks include:
• Unknown – The task for wells that contain a sample with unknown target
quantities.
• NTC – The task for wells that contain water or buffer instead of sample (no
template controls). No amplification of the target should occur in negative
control wells.
5. Repeat steps 3 and 4 as needed.
6. Once you have completed making changes to the plate layout, click Analyze to
reanalyze your project.
Applied Biosystems™ Relative Quantitation Analysis Module
27
4
Chapter 4 Edit experiment properties
Template files
Template files
The Applied Biosystems™ Analysis Software allows you to apply plate layout
information (such as the target, sample, and task configurations) from template files
that you can create using a text editor or spreadsheet application. Template files are
comma-separated value (.csv) files that contain the target, sample, and task
configurations for a single reaction plate. You can create a template file using a
spreadsheet application or a text editor, then import it using the Applied Biosystems™
Software to apply target, sample, and/or task information to experiments added to a
project.
If you have already added an experiment to your project, you can download a
template file that you can use as a starting point to create your own template files. The
following figure illustrates the general structure of the exported file.
A
Experiment
data
(do not edit):
Column
headings
(do not edit):
Plate setup
content (add
well data in any
order):
B
C
D
E
1
* Block Type = 96-Well
Block (0.2mL)
2
* Experiment Type =
Relative Quantitation
3
* Instrument Type =
7900HT Real-Time PCR
System
4
* No. Of Wells = 96
5
Set Up Well Section Inf
6
Well
Well Position
Sample Name
Task
Target Name
7
80
G9
Testes3
UNKNOWN
Hs00169663_m
1
8
95
H12
Testes3
UNKNOWN
Hs00608224_m
1
9
14
B3
Testes1
UNKNOWN
Hs00609297_m
1
…
…
…
…
… …
Use the following guidelines when editing the file:
• Rows 1 to 6 contain file header information that describes the experiment. In
general, you should not edit this information as it will be identical for all files that
you use. Enter the headings exactly as shown, including upper- and lowercase
letters:
– * Block Type =
– * Experiment Type =
– * Instrument Type =
– * No. Of Wells =
– * Set Up Well Section Info =
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Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 4 Edit experiment properties
Apply plate setup information using a template file
4
– Well
– Well Position
– Sample Name
– Task
– Target Name
• Rows 7 and below contain the plate setup information for the experiment, where
each row contains the information for the contents of a single well on the reaction
plate. As shown in the example above, the rows can occur in any order, but the
location information (in columns 1 and 2) must be accurate.
For each well the file contains the following information:
– Column A (Well) – The numerical position of the well on the plate, where
wells are numbered left to right and top to bottom. For example, on a 96-well
plate, the number of well A1 is "0" and the number of well G12 is "95".
– Column B (Well Position) – The coordinates of the well on the plate.
Note: For OpenArray™ plates, wells are identified through the combination
of the sector coordinates on the plate, and the coordinates of the well within
the sector. For example, the position "b2d10" refers to the through-hole at
position D10 within sector B2 on the plate.
– Column C (Sample Name) – The name of the sample within the well (up to
256-characters).
– Column D (Task) – The task of the sample within the well, where acceptable
values include UNKNOWN or NTC.
– Column E (Target Name) – The name of the assay added to the well, or the
identity of the target sequence (up to 256-characters).
• If the samples and/or targets that you include in the template file are present in
other experiments included in the project, the names in the file must match those
in the other experiments exactly (including case) in order for the software to
associate the data.
• When importing plate setup information from a template file, the Applied
Biosystems™ Software overwrites all existing settings with the information in the
file.
Apply plate setup information using a template file
The Applied Biosystems™ Software can import plate layout information directly from
design files that you can create using a text editor or spreadsheet application.
Note: For detailed information on the structure of template files, see “Template
files“ on page 28.
From the Plate Setup screen, you can perform the following actions:
• Download the plate setup information from an existing experiment as a template
file:
a. Open the project that includes the experiment with the desired plate layout,
then select Plate Setup.
b. From the Plate Setup screen, select the experiment record that contains the
desired plate setup.
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29
4
Chapter 4 Edit experiment properties
Apply plate setup information using a template file
c. From the Edit Plate screen, click Actions4Apply Template, then save the
file to the desired location.
• Apply plate setup information using a template file.
a. Create a template file that contains the desired plate setup information.
Note: See “Template files“ on page 28 for detailed information on
constructing template files.
b. Open the project that includes the experiment to which you want to apply
the template, then click Plate Setup.
c. From the Plate Setup screen, select the experiment record that you want to
modify.
d. From the Edit Plate screen, click Actions4Download Template.
e. Select the template file that contains the desired plate setup, then click Open.
If the import is successful, the sample, assay/target, and task assignments of the
current plate layout are overwritten with the imported settings.
IMPORTANT! The imported plate layout overrides the existing plate setup and
cannot be undone once imported.
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5
Review the raw data
■
■
■
■
Review the quality data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
Using the Amplification Plot Histogram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
About the quality data summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
Omit wells from the analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
After adding experiments to your project, use the Data Review screen to make a first
quality pass of your analyzed project data. The plots and features of the screen can
help you review your project for irregular amplification and other common PCR
problems.
Review the quality data
After the Applied Biosystems™ Analysis Software processes your project, you can use
the Data Review screen to review the quality data generated by the analysis. The
software provides a variety of options to review the quality data; however, the
strategy that you employ will depend on the type of quantitation you are performing
and the samples/targets that you are evaluating. The following procedure describes a
general approach to data review and provides an overview of the software features.
1. If you have not already done so, click Analyze to analyze your project.
2. In the Applied Biosystems™ Software, click Data Review to view the Data
Review screen.
3. From the drop-down list at the top of the screen, choose the way that you would
like to organize and review the quality data:
• Targets – Groups and displays the quality data by target name.
• Samples – Groups and displays the quality data by sample name.
• Plates – Groups and displays the quality data by experiment/plate.
Note: The Plates view is common to all real-time instrument software
manufactured by Thermo Fisher Scientific.
4. Review the amplification plots for irregularities and quality flags.
Note: The Applied Biosystems™ Software displays summaries of the quality
data in the margin beneath each amplification plot. You can view the identity of
any flag by hovering the mouse over the flag of interest.
5. If flags or irregularities are present, or you would just like to review the
amplification data for a specific target, sample, or experiment, click the
amplification plot of interest to zoom the display.
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Chapter 5 Review the raw data
Review the quality data
6. Configure the display options for the amplification plot. Click
from the available options:
Group
Plot
Type
Graph
Type
Color
Type
, then select
Select…
Description
dRn vs
Cycle
Displays ΔRn as a function of cycle number, where ΔRn is the
magnitude of normalized fluorescence signal generated by the
reporter at each cycle during the PCR amplification. You can
use this plot to identify and examine irregular amplification
and to view threshold and baseline values for the run.
Rn vs
Cycle
Displays Rn as a function of cycle number, where Rn is the
fluorescence signal from the reporter dye normalized to the
fluorescence signal from the passive reference. You can use
this plot to identify and examine irregular amplification.
CT vs
Well
Displays CT (Cq) as a function of well position, where CT is the
PCR cycle number at which the fluorescence meets the
threshold in the amplification plot. You can use this plot to
locate outlying amplification (outliers).
Linear
Displays the data on a linear scale.
Log
Displays the data on a logarithmic scale.
Well
Colors the data for each well according to its position on the
reaction plate.
Sample
Colors the data for each well according to the sample that it
contains.
Flag
Status
Colors the data for each well according to whether it generates
quality flags.
Amp
Status
Colors the data for each well according to the amplification
status that it is assigned.
7. If the amplification plot that you are viewing includes data from more than
384 wells, use the histogram beneath the Amplification Plot to view the data of
interest:
• Click and drag the anchor icon ( ) to the desired location in the histogram
to display the curves from the 384 wells with values nearest to the position
of the icon.
• Select the heading of a column in the Well Table that contains numerical
content (such as, Amp Score or CT/CRT without Flags) to change the x-axis
content of the histogram.
Note: Selecting the heading of a column in the Well Table that contains less than
384 data points hides the histogram. The feature is present only when the plot
contains more than 384 amplification curves.
8. If the data set that you are viewing consists of a large number of data points, use
the Outlier Wheel to organize, filter, and review the data for irregular
amplification:
a. In the right-side pane of the Review Plate screen, select View By4Outlier
Wheel.
b. From the Sort By dropdown list, select the attribute by which you want the
Applied Biosystems Software to filter the displayed data set.
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Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 5 Review the raw data
Review the quality data
5
c. While viewing the data set within the Outlier Wheel, select a segment of the
wheel to view the associated data within the Amplification Plot and Well
Table.
Note: Click the center of the wheel to deselect the data.
d. If desired, double-click a segment of the Outlier Wheel to review the related
subset of the displayed data.
As you select and filter the displayed data, the Applied Biosystems Software
lists the filters that you apply at the bottom of the Outlier Wheel Plot. To
remove a filter, either click Undo to remove the last filter applied or click the
X beside a desired filter to remove it.
e. At any time while reviewing your data, click Show Table to view the
tabular data for the datapoints present in the Outlier Wheel Plot.
See “Outlier Wheel Plot“ on page 62 for more information on the Outlier Wheel
plot.
9. Review the amplification plots as needed.
When reviewing the amplification data, look for:
• Regular, characteristic amplification of all samples. If irregular amplification
is present, consider omitting the individual wells from the analysis.
• Correct baseline and threshold values. If not, consider manually adjusting
the baseline and/or threshold values in the analysis settings.
10. When ready, click Multicomponent to review the multicomponent plot as
needed.
When reviewing the multicomponent plot, look for:
• Consistent fluorescence of the passive reference. The passive reference dye
fluorescence level should remain relatively constant throughout the PCR
process.
• Consistent fluorescence of the reporter dye. The reporter dye fluorescence
level should display a flat region corresponding to the baseline, followed by
a rapid rise in fluorescence as the amplification proceeds.
• Irregular fluorescence. There should not be any spikes, dips, and/or sudden
changes in the fluorescence.
• No amplification in negative control wells. There should not be any
amplification in the negative control wells.
11. View and modify the data in the Well table:
Tool
Use this tool to...
To select:
• An individual well, select the well in the Well table.
Mouse/cursor
• More than one well at a time, press the Ctrl key or Shift key when you select the wells in
the Well table.
When you select wells in the Results table, the corresponding data points are selected in the
amplification plot.
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Chapter 5 Review the raw data
Review the quality data
Tool
Group by drop-down
menu
Use this tool to...
Select how to group the samples in the Well table. For example, if you select Target, the
samples are grouped according to the nucleic acid sequence they target.
Bookmark/Clear Bookmark for wells in the project.
The bookmarks persist in the Data Review and Results screens, so you can easily find
bookmarked wells.
Actions drop-down
list
Omit/UnOmit well from the analysis.
After you omit or un-omit a well, click Analyze to reanalyze the project.
For omitted wells, the software:
• Does not display data or tasks in the Well table.
• Does not include the omitted wells in the analysis.
For un-omitted wells, the software reassigns the tasks based on the settings in the Analysis
Settings dialog box.
Flag Details
or
Select Show Flag Details to display the results of each quality flag in an individual column.
When unselected, the table displays the results of the quality analysis in a single column.
Expand or collapse the Well table.
12. Review the data in the Well table data.
Column
Use this column to...
(Bookmark) View whether or not the well has been bookmarked.
Omit
CT /CRT
View the omission status of the related well.
View the CT /CRT calculated for the related well.
Amp Status
View the amplification status as determined by the software, where
possible states are amplification, no amplification, reviewed, and
undetermined.
Amp Score
View the amplification score calculated for the well.
Cq Conf
View the confidence value calculated by the software for the CQ (CT)
for the given well.
Sample
View the ID (a unique name or number) of the sample.
Target
View the ID (a unique name or number) of the nucleic acid
sequence targeted by the assay added to the well.
Well
View the location of the well in the reaction plate. For example, P18
indicates that the sample is located in row P, column 18.
Plate
View the barcode of the reaction plate used to run the reaction. If
no barcode is present, the software displays the name of the
experiment file to which the data belongs.
Baseline Start View the start and endpoints of the range of PCR cycles used as
Baseline End the baseline in the calculation the CT for the related well.
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Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 5 Review the raw data
Review the quality data
Column
Task
5
Use this column to...
View the task assigned to the well. A task is the function that a
sample performs:
• Unknown
• No template control (NTC) (control identifier)
Flags
View the number of flags generated for the well.
13. When ready, click
to return to the QC thumbnails.
14. Review the amplification data for specific targets, samples, or experiments as
needed.
in the toolbar to review the quality summary.
15. Click
Review the Quality Summary for any flags generated by the project data. For
each quality flag, the table displays the number of times the flag was triggered by
the project data. To examine the data that triggered the flag, click the link in the
Name column to view the amplification data for the related target, sample, or
plate.
In response to the presence of quality flags, consider the following resolutions:
• Change the quality settings in the analysis group:
– Adjust the sensitivity of the quality flags so that more wells or fewer
wells are flagged.
– Deactivate the quality flags that triggered by the data.
• Omit individual wells from the analysis.
Applied Biosystems™ Relative Quantitation Analysis Module
35
5
Chapter 5 Review the raw data
Using the Amplification Plot Histogram
Using the Amplification Plot Histogram
When an Amplification Plot for a specific sample, target, or plate includes data for
more than 384 data points, the Applied Biosystems™ Software displays a subset of the
data (shown in color) for active viewing against a background of the full dataset
(shown in grey). The range of active data in the plot is controlled through a histogram
of a numerical attribute associated with the well data, which is located beneath the
plot (see below).
• Click and drag the anchor icon ( ) to the desired location in the histogram to
display the curves from the 384 data points with values nearest to the position of
the icon.
• Select the heading of a column in the Well Table that contains numerical content
(such as, Amp Score or CT/CRT without Flags) to change the x-axis content of the
histogram.
Note: Selecting the heading of a column in the Well Table that contains less than
384 data points hides the histogram. The feature is present only when the plot
contains more than 384 amplification curves.
About the quality data summary
The quality summary displays a table of the quality flags supported by the software.
For each sample, target, or plate, the table lists the flag frequency and location for any
experiment that is added to a project. For each quality flag, the table displays the
number of times the flag was triggered by the project data. To examine the data that
triggered the flag, click the link in the Name column to view the amplification data for
the related target, sample, or plate.
In response to the presence of quality flags, consider the following resolutions:
• Change the quality settings in the analysis group:
– Adjust the sensitivity of the quality flags so that more wells or fewer wells
are flagged.
– Deactivate the quality flags that triggered by the data.
• Omit individual wells from the analysis.
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Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 5 Review the raw data
Omit wells from the analysis
5
Omit wells from the analysis
To omit the data from one or more wells that you do not want included in the
analysis:
• Select one or more wells in a plot or table, then click Actions4Omit. After the
wells are omitted, click Analyze to reanalyze the project without the omitted
well(s).
IMPORTANT! You cannot omit all wells that belong to a reference sample, that
belong to a biological group, or that serve as the endogenous control for the project.
Note: To restore an omitted well, select the well from a plot or table, then
select Actions4UnOmit.
Applied Biosystems™ Relative Quantitation Analysis Module
37
6
Review the analyzed data
■
■
■
■
■
■
■
■
Review the analyzed data and plots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
Box Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
Correlation Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
RQ Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
Heatmap Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Volcano Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
Melt Curve Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
Omitting wells and samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
After reviewing the data, use the Analysis screen to review the results of the analyzed
project. The screen provides a variety of plots to help you characterize the analyzed
data and to better visualize the relationships between the calculated expression of the
evaluated targets.
Review the analyzed data and plots
After you have reviewed the quality data for your project, view the results of the
analysis in the Analysis screen. As with the quality check, the following procedure
describes a general approach to data review and provides an overview of the software
features.
1. If you have not already done so, click Analyze to analyze your project.
2. In the Applied Biosystems™ Software, click Analysis to view the Analysis screen.
Box Plot as needed (see “Box Plot“ on page 42).
3. Review the
a. Click View Options, then select CT vs Sample from the Plot Type dropdown list.
b. Click the magnification factor to determine the percentage of the plot
displayed onscreen at once.
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Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 6 Review the analyzed data
Review the analyzed data and plots
6
c. Scroll down to review the data in the Well table data.
Column
Sample
Biological
Group
Mean
Use this column to...
View the ID (a unique name or number) of the sample.
View the biological group (a unique name or number) to which
the sample belongs.
View the arithmetic average of the technical replicate CT
values.
Min
View the minimum technical replicate CT value for the test
sample calculated using the confidence level set in the
analysis settings.
Max
View the maximum technical replicate CT value for the test
sample calculated using the confidence level set in the
analysis settings.
Median
View the median CT value for the technical replicates of the
sample.
Q1
Q3
View the 1st Quartile (Q1) for the sample replicate group, which
is calculated as the numeric midpoint between the lowest and
median CT values of the technical replicates.
Note: The 1st Quartile defines lower boundary of the interquartile region (IQR), which is defined as the difference
between the 3rd and 1st quartile.
View the 3rd Quartile (Q3) for the sample replicate group, which
is calculated as the numeric midpoint between the median and
maximum CT values of the technical replicates.
Note: To filter the table data, click
(Filter) within any column heading,
configure the rules as desired, then click Filter.
Note: If desired, you can view the quality data for any selected sample or well
by selecting the element in the plot or table and clicking View QC.
to review the Correlation Plot as needed (see “Correlation
4. When ready, click
Plot“ on page 42).
a. If you are using biological groups and more than 100 samples are present in
the analysis group currently in use, select a group from the drop-down list
to view the corresponding data.
b. Click View Options, then select the data arrangement that you want to view
(Matrix View or Tabular View).
c. Select the type of plot that you want to display (CT or ∆CT)
to review the Heatmap Plot as needed (see “Heatmap
5. When ready, click
Plot“ on page 45).
a. Click View Options, then select the distance measure (Euclidean Distance
or Pearson's Correlation) from the Distance Measure drop-down menu.
b. Select the clustering method (Average Linkage, Complete Linkage, or Single
Linkage) from the Clustering Method drop-down menu.
Applied Biosystems™ Relative Quantitation Analysis Module
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6
Chapter 6 Review the analyzed data
Review the analyzed data and plots
c. Change the plot type from the Map Type menu. Select a data display option
(Global (∆CT), Global (∆CT Plus), Sample-centric, or Target-centric) from the
Map Type drop-down menu.
d. Select a color scheme (Red Blue, Red Green, or Green Orange) from the
Color Scheme drop-down menu.
to review the Relative Quantitation Plot as needed (see “RQ
6. When ready, click
Plot“ on page 43).
a. Click View Options, then select a data display option (RQ vs Sample, RQ vs
Biological Group or RQ vs Target) from the Plot Type drop-down menu.
b. Change the graph type by selecting a plot scale (Linear, Log 10, Log 2, or Ln)
from the Graph Type drop-down menu.
c. Change the plot options:
• To view error bars showing RQ Max and RQ Min, select Show Error
Bars.
• To view labels on the graph, select the appropriate label option.
d. Click the magnification factor to determine the percentage of the plot
displayed onscreen at once.
e. Scroll down to review the data in the Well table data.
Column
Use this column to...
Target
View the ID (a unique name or number) of the nucleic acid sequence targeted by the assay.
Sample
View the ID (a unique name or number) of the sample.
Biological Group
Max CT/CRT
CT/CRT Mean
Adjusted CT/CRT Mean
CT/CRT SE
View the biological group (a unique name or number) to which the sample belongs.
View the maximum Cq defined by the "Maximum allowed CT" limit in the RQ Settings analysis
settings.
View the arithmetic average of the technical replicate Cq values.
View the average of the technical replicate Cq values that have been adjusted based on the
"Maximum allowed CT" limit defined in the RQ Settings analysis settings.
Note: Wells with Cq scores greater than the "Maximum allowed CT" value are adjusted to the
specified Cq limit.
View the sample standard deviation of the sample replicate group level Cq values.
View the arithmetic average of the technical replicate Cq values for the sample replicate
group.
∆CT/∆CRT Mean
Note: The ∆CT/∆CRT mean is calculated at the reaction plate level and represents the mean
difference between the target Cq values and the endogenous control Cq values for all the
technical replicates for that sample that are present on the plate.
View the sample standard deviation of the sample replicate group level Cq values.
∆CT/∆CRT SE
40
Note: The ∆CT/∆CRT SE value is calculated differently for multiplex and singleplex
experiments. For multiplex experiments, the calculation is at the well level. For singleplex
experiments, the calculation combines the plate-level Cq value variation between the target
and the endogenous control.
Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 6 Review the analyzed data
Review the analyzed data and plots
Column
6
Use this column to...
View the calculated F-Factor for the replicate group associated with the reference sample.
The F-Factor is used to calculate the RQ confidence intervals in the ∆∆CT calculation
(displayed as error bars in the RQ plot). The value is calculated differently depending on the
RQ Settings in the analysis settings for your project.
F-Factor
• If you specified a Confidence level setting, then the F-Factor is the t-value of the
Student's t-distribution calculated from the:
– Degrees of freedom that characterize the distribution of the replicate population. If
the project contains no biological groups, degrees of freedom is calculated per
Technical Test Sample as:
#Technical Replicates WellsTarget + #Technical Replicates WellsEndo - 2.
Otherwise, the value is calculated per Biological Test Sample as:
#Technical Replicates Groups Test Sample - 1.
– Probability associated with the two-tailed Student's t-distribution (determined by
the RQ Settings in the analysis settings for your project).
• If you specified a Limit by standard deviations setting, then the F-Factor is equal to the
setting (1, 2, or 3).
∆∆CT/∆∆CRT
View the calculated ΔΔCT value for the replicate group associated with the reference sample.
∆∆CT/∆∆CRT ± FSigma
View the calculated ΔΔCT value added to or subtracted from the F-Sigma value calculated for
the replicate group associated with the reference sample.
RQ
View the calculated relative level of gene expression for the replicate group that is associated
with the test sample.
RQ Min
RQ Max
View the minimum relative level of gene expression in the test samples calculated using the
confidence level set in the analysis settings.
Note: The minimum includes the variability associated with the endogenous control and
targets in only the test samples.
View the maximum relative level of gene expression in the test samples calculated using the
confidence level set in the analysis settings.
Note: The maximum includes the variability associated with the endogenous control and
targets in only the test samples.
Note: To filter the table data, click
(Filter) within any column heading,
configure the rules as desired, then click Filter.
7. When ready, click
Plot“ on page 46).
to review the Volcano Plot as needed (see “Volcano
Applied Biosystems™ Relative Quantitation Analysis Module
41
6
Chapter 6 Review the analyzed data
Box Plot
Box Plot
The box plot displays the distribution of Cq values for each sample or for each target,
making it easy to view the variation in values among biological groups.
Below the box plots is the Results Details table, showing the following information:
Column
Sample
Biological Group
Mean
Use this column to...
View the ID (a unique name or number) of the sample.
View the biological group (a unique name or number) to which the
sample belongs.
View the arithmetic average of the technical replicate Cq values.
Min
View the minimum technical replicate Cq value for the test sample
calculated using the confidence level set in the analysis settings.
Max
View the maximum technical replicate Cq value for the test sample
calculated using the confidence level set in the analysis settings.
Median
View the median Cq value for the technical replicates of the sample.
Q1
Q3
View the 1st Quartile (Q1) for the sample replicate group, which is
calculated as the numeric midpoint between the lowest and median Cq
values of the technical replicates.
Note: The 1st Quartile defines lower boundary of the inter-quartile
region (IQR), which is defined as the difference between the 3rd and 1st
quartile.
View the 3rd Quartile (Q3) for the sample replicate group, which is
calculated as the numeric midpoint between the median and maximum
Cq values of the technical replicates.
Changing the Box
Plot display
Correlation Plot
The Correlation plots display the correlation between the target genes in one or more
samples or biological groups. There are two correlation plots: the scatter plot and the
signal correlation plot.
• The scatter plot shows the correlation of Cq for all targets for a pair of samples or
biological groups.
• The signal correlation plot shows the correlation coefficient (r) for all pairs of
samples or biological groups in the project. The plot is color-coded based on |r|,
(the absolute value of r), indicating the strength of the correlation: green indicates
highly correlated (either negative or positive) and red indicates low correlation
(either negative or positive). Each cell represents a different scatter plot.
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Chapter 6 Review the analyzed data
RQ Plot
6
RQ Plot
The RQ (Relative Quantitation) Plot displays the results of the relative quantitation
calculations in the gene expression profile. Three plots are available:
• RQ vs Target – Groups the relative quantitation (RQ) values by target. Each
sample is plotted for each target. You can view the plot as the following graph
types: linear, log10, Ln, log2.
• RQ vs Sample (present when the plot displays results by Samples) – Groups the
relative quantitation (RQ) values by sample. Each target is plotted for each
sample. You can view the plot as the following graph types: linear, log10, Ln,
log2.
• RQ vs BioGroup – (present when the plot displays results by Biogroups) –
Groups the relative quantitation (RQ) values by biological replicate group. Each
target is plotted for each sample. You can view the plot as the following graph
types: linear, log10, Ln, log2.
IMPORTANT! If one or more assay efficiencies are set less than 100%, then the
Applied Biosystems™ Software performs the gene expression calculation using
equivalent Cq values, where the software adjusts the Cqs of each target proportionally
to achieve equivalent efficiency. The resulting equivalent Cqs calculated for the
affected targets reflect the values expected if the assays performed at 100% efficiency.
Below the gene expression plot is the Results Details table, showing the following
information:
Column
Use this column to...
Target
View the ID (a unique name or number) of the nucleic acid sequence targeted by the assay.
Sample
View the ID (a unique name or number) of the sample.
Biological Group
Max CT/CRT
CT/CRT Mean
Adjusted CT/CRT Mean
CT/CRT SE
View the biological group (a unique name or number) to which the sample belongs.
View the maximum Cq defined by the "Maximum allowed CT" limit in the RQ Settings analysis
settings.
View the arithmetic average of the technical replicate Cq values.
View the average of the technical replicate Cq values that have been adjusted based on the
"Maximum allowed CT" limit defined in the RQ Settings analysis settings.
Note: Wells with Cq scores greater than the "Maximum allowed CT" value are adjusted to the
specified Cq limit.
View the sample standard deviation of the sample replicate group level Cq values.
View the arithmetic average of the technical replicate Cq values for the sample replicate
group.
∆CT/∆CRT Mean
Note: The ∆CT/∆CRT mean is calculated at the reaction plate level and represents the mean
difference between the target Cq values and the endogenous control Cq values for all the
technical replicates for that sample that are present on the plate.
Applied Biosystems™ Relative Quantitation Analysis Module
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6
Chapter 6 Review the analyzed data
RQ Plot
Column
Use this column to...
View the sample standard deviation of the sample replicate group level Cq values.
∆CT/∆CRT SE
F-Factor
View the calculated F-Factor for the replicate group associated with the reference sample.
∆∆CT/∆∆CRT
View the calculated ΔΔCT value for the replicate group associated with the reference sample.
∆∆CT/∆∆CRT ± FSigma
View the calculated ΔΔCT value added to or subtracted from the F-Sigma value calculated for
the replicate group associated with the reference sample.
RQ
View the calculated relative level of gene expression for the replicate group that is associated
with the test sample.
RQ Min
RQ Max
44
Note: The ∆CT/∆CRT SE value is calculated differently for multiplex and singleplex
experiments. For multiplex experiments, the calculation is at the well level. For singleplex
experiments, the calculation combines the plate-level Cq value variation between the target
and the endogenous control.
View the minimum relative level of gene expression in the test samples calculated using the
confidence level set in the analysis settings.
Note: The minimum includes the variability associated with the endogenous control and
targets in only the test samples.
View the maximum relative level of gene expression in the test samples calculated using the
confidence level set in the analysis settings.
Note: The maximum includes the variability associated with the endogenous control and
targets in only the test samples.
Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 6 Review the analyzed data
Heatmap Plot
6
Heatmap Plot
The heat map is a representation of the level of expression of many targets (genes)
across a number of samples. The targets and samples are arranged according to the
similarity of their gene expression.
Below the Heatmap Plot is the Results Details table, showing the following
information:
Column
Sample
Biological Group
Target
CT/CRT Mean
Adjusted CT/ CRT
Mean
Use this column to...
View the ID (a unique name or number) of the sample.
View the biological group (a unique name or number) to which the sample belongs.
View the ID (a unique name or number) of the nucleic acid sequence targeted by the assay.
View the arithmetic average of the technical replicate Cq values.
View the average of the technical replicate Cq values that have been adjusted based on the
"Maximum allowed CT" limit defined in the RQ Settings analysis settings.
Note: Wells with Cq scores greater than the "Maximum allowed CT" value are adjusted to the
specified Cq limit.
View the arithmetic average of the technical replicate ∆Cq values for the sample replicate
group.
∆CT/∆CRT Mean
Note: The ∆CT/∆CRT mean is calculated at the reaction plate level and represents the mean
difference between the target ∆CT/∆CRT values and the endogenous control ∆CT/∆CRT values
for all the technical replicates for that sample that are present on the plate.
View the sample standard deviation of the sample replicate group level Cq values.
∆CT/∆CRT SE
∆CT/∆CRT + Control
Median
Note: The ∆CT/∆CRT SE value is calculated differently for multiplex and singleplex
experiments. For multiplex experiments, the calculation is at the well level. For singleplex
experiments, the calculation combines the plate-level Cq value variation between the target
and the endogenous control.
View the arithmetic average of the technical replicate ∆CT/∆CRT values for the sample
replicate group added to the control median.
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Chapter 6 Review the analyzed data
Volcano Plot
Volcano Plot
The volcano plot displays the p-value versus the fold change for each target in a
biological group, relative to the reference group. Green and red dots represent targets
with a fold change outside (greater or lesser than) the fold change boundary. Compare
the size of the fold change (x-axis) to the statistical significance level (y-axis) on the
volcano plot.
Note: You must have biological groups assigned (so that p-values can be calculated)
before you can view data on the volcano plot.
IMPORTANT! If one or more assay efficiencies are set to <100%, then the Applied
Biosystems™ Software performs the gene expression calculation using equivalent Cq
values, where the software adjusts the Cqs of each target proportionally to achieve
equivalent efficiency. The resulting equivalent Cqs calculated for the affected targets
reflect the values expected if the assays performed at 100% efficiency.
Below the plot is the Results Details table, showing the following information:
Column
Biological Group
Target
CT/CRT Mean
Adjusted CT/CRT Mean
Use this column to...
View the biological group (a unique name or number) to which the sample belongs.
View the ID (a unique name or number) of the nucleic acid sequence targeted by the assay.
View the arithmetic average of the technical replicate Cq values.
View the average of the technical replicate Cq values that have been adjusted based on the
"Maximum allowed CT" limit defined in the RQ Settings analysis settings.
Note: Wells with Cq scores greater than the "Maximum allowed CT" value are adjusted to the
specified Cq limit.
View the arithmetic average of the technical replicate Cq values for the sample replicate
group.
∆CT/∆CRT Mean
Note: The ∆CT/∆CRT mean is calculated at the reaction plate level and represents the mean
difference between the target Cq values and the endogenous control Cq values for all the
technical replicates for that sample that are present on the plate.
View the sample standard deviation of the sample replicate group level Cq values.
∆CT/∆CRT SE
∆∆CT/∆∆CRT
View the calculated ΔΔCT value for the replicate group associated with the reference sample.
RQ
View the calculated relative level of gene expression for the replicate group that is associated
with the test sample.
RQ Min
46
Note: The ∆CT/∆CRT SE value is calculated differently for multiplex and singleplex
experiments. For multiplex experiments, the calculation is at the well level. For singleplex
experiments, the calculation combines the plate-level Cq value variation between the target
and the endogenous control.
View the minimum relative level of gene expression in the test samples calculated using the
confidence level set in the analysis settings.
Note: The minimum includes the variability associated with the endogenous control and
targets in only the test samples.
Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 6 Review the analyzed data
Volcano Plot
Column
RQ Max
6
Use this column to...
View the maximum relative level of gene expression in the test samples calculated using the
confidence level set in the analysis settings.
Note: The maximum includes the variability associated with the endogenous control and
targets in only the test samples.
P-Value
View the probability (P-value) that the observed RQ (fold change) in gene expression for the
replicate group associated with the test sample is not differentially expressed due to
treatment or condition.
Result
View the assignment for the replicate group that is associated with the test sample, where
possible states are: down-regulated, up-regulated, insignificant, or flat.
View and modify
the Volcano Plot
The Applied Biosystems™ Software allows you to view the gene expression data in
volcano plot that displays the p-value statistics data for each biological group.
1. View details of the Volcano Plot:
a. In the Analysis screen, click
b. Move the pointer over a point to view information about it.
2. If necessary, change the group displayed in the plot:
From the Group drop-down menu, select a different group to compare to the
reference group.
3. If necessary, change the boundaries displayed on the plot. To change the:
• Fold-change Boundary (x-axis) – Enter a number greater than or equal to 1 in
the Fold Change Boundary field, then click Apply.
Targets having a fold change greater than the upper boundary are colored
red; targets with a fold change less than the lower boundary are colored
green.
• P-value Boundary (y-axis) – Enter a number from 0 to 1 in the P-Value
Boundary field, then click Apply.
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Chapter 6 Review the analyzed data
Melt Curve Plot
Melt Curve Plot
The melt curve plot (also called a dissociation curve plot) displays data collected
during a melt curve stage. Peaks in the melt curve can indicate the melting
temperature (Tm) of a target or can identify nonspecific PCR amplification. The
software displays the melt curve plot only for those experiments with a PCR method
that includes a melt curve stage (a gradual temperature ramp configured for data
collection).
Two views are available:
• Normalized reporter (Rn) vs. temperature — The normalized reporter view
visualizes the rise in fluorescence throughout the temperature ramp. The
normalized reporter (Rn), displayed on the y-axis, is calculated as the
fluorescence signal from the reporter dye normalized to the fluorescence signal of
the passive reference.
• Derivative reporter (−Rn′) vs. temperature — The derivative reporter view
allows you to visualize the maximum rate of change in fluorescence during the
temperature ramp. The derivative reporter, displayed on the y-axis, is calculated
as the negative first derivative of the normalized fluorescence (Rn) generated by
the reporter during PCR amplification.
Omitting wells and samples
You may omit wells from analysis if you do not want to consider data generated by
the well.
1. Select one or more wells to omit from analysis.
2. Omit the selected wells:
• Well Table tab - Select the wells, then select Actions4Omit.
• Plate Layout tab - Select the wells, then click Omit.
3. Click Analyze to reanalyze the data without the omitted wells.
IMPORTANT! You cannot omit all wells that belong to a reference sample, that
belong to a biological group, or that serve as the endogenous control for a project.
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Applied Biosystems™ Relative Quantitation Analysis Module
7
Export the results
■
■
■
■
Export the analyzed data from a project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
Export project data as a slide presentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
Export plots for presentation and publication . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
Export data for use in other projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
After you are finished analyzing your project, you can use the Applied Biosystems™
Analysis Software to publish the project data.
Export the analyzed data from a project
The Applied Biosystems™ Analysis Software allows you to export project data as
comma-separated or tab-delimited text, which can be imported by most spreadsheet
applications for further analysis or presentation.
1. From the main menu of the project that contains data to export, click Export.
2. From the Export screen, click , then enter the following information:
a. Enter a name for the exported report in the Name field.
Note: Naming the report will allow you to repeat the export if you need to
do so again.
b. Select the file type for the exported data:
• .txt - To export data to a tab-delimited text file.
• .csv - To export data to a comma-separated text file.
c. (CSV and TXT exports only) Select the check boxes for the data that you want
to export.
• Biological Group Results - Exports gene expression analysis results
organized and analyzed by biological group.
• Sample Results - Exports gene expression analysis results organized
and analyzed by individual samples.
• Well Results - Exports gene expression analysis results for the
individuals wells of every reaction plate used in the analysis.
• Amplification Data - Exports amplification results for each well in the
project, such as cycle numbers, and Rn or ΔRn values.
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Chapter 7 Export the results
Export project data as a slide presentation
• Volcano Plot Data - Exports gene expression data used to generate the
Volcano Plot, including Fold Change, P-Value, Fold Change Boundary,
P-Value Boundary, and the Result.
• Targets/Samples/Plates QC (with flags) - Exports a summary of the
quality metrics (flags) generated by the data analysis. The option allows
you to selectively export the quality data organized by target, sample,
or plate.
3. If you want to customize the export to include specific data, click
Actions4Customize, then select the data columns that you want to export from
each selected tables.
4. From the Export Details screen, select the fields from the data tables to include in
the exported file, then click Start Export.
After starting the export, wait for the Applied Biosystems™ Analysis Software to
generate the report. The export is complete when the Status column of the
exported report displays "Download".
After generating the data export, the Applied Biosystems™ Software displays the
package as a row in the Export History table.
5. (Optional) Click the entry in the Comments column, then enter any additional
information for the exported report.
6. Click Download, select the location for the exported data file, then click Save.
Once generated, a data export package remains in the Export History indefinitely or
until you remove it. To delete a package, select an export package from the table, then
click Actions and select Delete File(s).
Export project data as a slide presentation
The Applied Biosystems™ Analysis Software allows you to export your project data as
a Microsoft™ PowerPoint® slide presentation. The exported file summarizes the project
data and saves the exported file in a generic template that you can override by
importing a Microsoft™ PowerPoint® template file.
1. From the main menu of the project that contains data to export, click Export.
2. From the Export screen, click , then enter the following information:
a. Enter a name for the exported report in the Name field.
Note: Naming the report will allow you to repeat the export if you need to
do so again.
b. From the File type menu, select .pptx.
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Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 7 Export the results
Export plots for presentation and publication
7
3. From the Export Details screen, select the fields from the data tables to include in
the exported file, then click Start Export.
After starting the export, wait for the Applied Biosystems™ Analysis Software to
generate the report. The export is complete when the Status column of the
exported report displays "Download".
After generating the data export, the Applied Biosystems™ Software displays the
package as a row in the Export History table.
4. (Optional) Click the entry in the Comments column, then enter any additional
information for the exported report.
5. Click Download, select the location for the exported data file, then click Save.
Once generated, a data export package remains in the Export History indefinitely or
until you remove it. To delete a package, select an export package from the table, then
click Actions and select Delete File(s).
You can use the Microsoft™ PowerPoint® Application to reformat the exported slide
presentation. For more information on applying a theme or template to your
presentation, refer to the Microsoft™ PowerPoint® Help.
Export plots for presentation and publication
The Applied Biosystems™ Analysis Software allows you to export any plot as a
Portable Network Graphics (.png) or Joint Photographic Expert Group (.jpg) file,
which can be imported by most spreadsheet and desktop publishing software for
presentation.
1. When viewing a plot, click
(Save as image) or select Actions4Save as Image.
2. Save the image.
a. Click the File Name field, then enter a name for the exported graphics file.
b. Select the appropriate file format (.png or .jpg).
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Chapter 7 Export the results
Export data for use in other projects
c. Click Download to download the plot image file, or click Add to
PowerPoint to add the plot to an exported PowerPoint presentation (see
“Export project data as a slide presentation“ on page 50).
3. In the Save As dialog box, select the location for the exported data file, then click
Save.
Export data for use in other projects
The Applied Biosystems™ Analysis Software allows you to export the following data
from a project for use in other analyses.
• Export a sample design file
A sample design file is a tab-or comma-delimited file (*.txt or *.csv) that contains
a list of sample names and the corresponding names of the biological groups to
which the samples belong. You can use exported sample design files to quickly
import the sample information into other experiments.
a. Open the project that contains experiment with the sample information of
interest, then click Overview.
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Chapter 7 Export the results
Export data for use in other projects
7
b. From the Samples table in the Overview screen, click Actions4Export
Design File.
c. In the Export Sample Settings dialog box, select the format for the exported
file (.txt or .csv), then click OK.
d. Select the location and name for the exported file, then click Save.
• Export a template file
Template files contain plate layout information (target, sample, and task
configurations) that you can use to easily set up experiments added to your
projects. The Applied Biosystems™ Software allows you to export template files
from existing experiments or to create them using a text editor or spreadsheet
application.
a. Open the project that includes the desired experiment, then select Plate
Setup.
b. From the Plate Setup screen, select the experiment record that contains the
plate setup information of interest.
c. From the Edit Plate screen, click Actions4Download Template, then save
the file to the desired location.
• Export the amplification efficiency settings
Amplification efficiency files associate targets with the specific amplification
efficiencies of the corresponding assays. Once exported, you can use the file to
import the settings to other projects (especially useful for projects involving large
numbers of targets).
a. Open the project that includes the analysis settings with the desired
efficiency data, then select Overview.
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Chapter 7 Export the results
Export data for use in other projects
b. From the Overview screen, select the analysis group that contains the
efficiency data, then click Edit Analysis Settings.
c. From the Analysis Settings dialog box, click Efficiency to view the assay
efficiency settings, then click Export.
d. In the Export Sample Settings dialog box, select the format for the exported
file (.txt or .csv), then click OK.
e. Select the location and name for the exported file, then click Save.
• Export the CT settings
The CT settings file associates targets with specific methods for calculating
baseline and threshold values (manual or automatic). Once exported, you can use
the file to import the settings to other projects (especially useful for projects
involving large numbers of targets).
a. Open the project that includes the analysis settings with the desired CT
settings, then select Overview.
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Chapter 7 Export the results
Export data for use in other projects
7
b. From the Overview screen, select the analysis group that contains the CT
settings, then select Action4Edit Analysis Settings.
c. From the Analysis Settings dialog box, click Cq Settings to view the Cq
settings, then click Export CT Settings.
d. In the Export CT Settings dialog box, select the format for the exported file
(.txt or .csv), then click OK.
e. Select the location and name for the exported file, then click Save.
Applied Biosystems™ Relative Quantitation Analysis Module
55
8
Screens and plots
■
■
■
■
■
■
■
■
■
■
Amplification Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
Box Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
Correlation Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Heatmap Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Melt Curve Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
Multicomponent Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
Outlier Wheel Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
RQ Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
Volcano Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
Well Table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
The Applied Biosystems™ Analysis Software provides the following screens and plots
that can be used to edit and visualize experiment setups and results that have been
added to your project.
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Chapter 8 Screens and plots
Amplification Plot
8
Amplification Plot
The Amplification Plot screen displays post-run amplification of the samples of each
experiment added to your project. Three plots are available:
• ΔRn vs Cycle – ΔRn is the magnitude of normalized fluorescence signal
generated by the reporter at each cycle during the PCR amplification (ΔRn = Rn –
baseline). This plot displays ΔRn as a function of cycle number. You can use this
plot to identify and examine irregular amplification and to view threshold and
baseline values for the run.
• Rn vs Cycle – Rn is the fluorescence signal from the reporter dye normalized to
the fluorescence signal from the passive reference. This plot displays Rn as a
function of cycle number. You can use this plot to identify and examine irregular
amplification.
• CT vs Well – CT (Cq) is the PCR cycle number at which the fluorescence meets the
threshold in the amplification plot. This plot displays CT as a function of well
position. You can use this plot to locate outlying amplification (outliers).
1
4
3
2
Toolbar – Contains the following tools for controlling the
plot:
– Select individual data points from the plot.
– Zoom the plot to the selected area.
– Zooms out the plot to show all data points.
– Saves the plot as an image (.png or .jpg).
– Allows you to adjust the display options for the plot.
2 Threshold – The threshold (calculated or manual) that is
currently applied to the project data.
1
Applied Biosystems™ Relative Quantitation Analysis Module
View Options – The view options for the Amplification
Plot. Use the drop-down lists to display the type of plot
displayed by the software (ΔRn vs Cycle, Rn vs Cycle, or
CT vs Well), the scale of the y-axis (log or linear), and the
color scheme for the plot.
4 Amplification curves – Normalized fluorescence for
individual wells throughout the course of the thermal
cycling protocol.
3
57
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Chapter 8 Screens and plots
Box Plot
Note: When the Amplification Plot displays a large data set, the Applied
Biosystems™ Software alters the appearance of curves to better identify them:
· Inactive data – Displayed using solid, grey curves
· Omitted data – Wells omitted automatically/manually are displayed using Longdashed, grey curves ( — — — )
· Unselected data – Wells not part of the current selection are displayed using shortdashed, grey curves ( - - - - - - )
Viewing large data sets
When an Amplification Plot for a specific sample, target, or plate includes data for
more than 384 data points, the Applied Biosystems™ Software displays a subset of the
data (shown in color) for active viewing against a background of the full data set
(shown in grey). The range of active data in the Amplification Plot is controlled
through a histogram, located beneath the plot, which displays the well data for the
experiment tabulated by an associated numerical attribute (such as Amp Score or
CT/CRT without Flags).
The position of the anchor icon ( ) in the histogram controls the range of active data
displayed by the Amplification Plot, where the software displays the curves from the
384 data points with values nearest to the position of the icon. To change the range of
active data, click and drag the icon to view the data nearest the desired location.
Note: Alternatively, click / below the Well Table to advance the active data range
displayed by the Amplification Plot.
The content of the histogram is determined by the table heading selected in the Well
Table. By default, the histogram tabulates data by Amp Score as shown above. To
change the data displayed on the x-axis of the histogram, select the heading of a
column in the Well Table that contains numerical content (such as, Amp Score or
CT/CRT without Flags).
Note: Selecting the heading of a column in the Well Table that contains less than 384
data points hides the histogram. The feature is present only when the plot contains
more than 384 amplification curves.
Box Plot
The box plot displays the distribution of Cq values for each sample or for each target,
making it easy to view the variation in values among biological groups.
Below the box plots is the Results Details table, showing the following information:
Column
Sample
Biological Group
Mean
Min
58
Use this column to...
View the ID (a unique name or number) of the sample.
View the biological group (a unique name or number) to which the
sample belongs.
View the arithmetic average of the technical replicate Cq values.
View the minimum technical replicate Cq value for the test sample
calculated using the confidence level set in the analysis settings.
Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 8 Screens and plots
Correlation Plot
Column
Use this column to...
Max
View the maximum technical replicate Cq value for the test sample
calculated using the confidence level set in the analysis settings.
Median
View the median Cq value for the technical replicates of the sample.
Q1
Q3
8
View the 1st Quartile (Q1) for the sample replicate group, which is
calculated as the numeric midpoint between the lowest and median Cq
values of the technical replicates.
Note: The 1st Quartile defines lower boundary of the inter-quartile
region (IQR), which is defined as the difference between the 3rd and 1st
quartile.
View the 3rd Quartile (Q3) for the sample replicate group, which is
calculated as the numeric midpoint between the median and maximum
Cq values of the technical replicates.
Correlation Plot
The Correlation plots display the correlation between the target genes in one or more
samples or biological groups. There are two correlation plots: the scatter plot and the
signal correlation plot.
• The scatter plot shows the correlation of Cq for all targets for a pair of samples or
biological groups.
• The signal correlation plot shows the correlation coefficient (r) for all pairs of
samples or biological groups in the project. The plot is color-coded based on |r|,
(the absolute value of r), indicating the strength of the correlation: green indicates
highly correlated (either negative or positive) and red indicates low correlation
(either negative or positive). Each cell represents a different scatter plot.
Heatmap Plot
The heat map is a representation of the level of expression of many targets (genes)
across a number of samples. The targets and samples are arranged according to the
similarity of their gene expression.
Below the Heatmap Plot is the Results Details table, showing the following
information:
Column
Sample
Biological Group
Target
CT/CRT Mean
Use this column to...
View the ID (a unique name or number) of the sample.
View the biological group (a unique name or number) to which the sample belongs.
View the ID (a unique name or number) of the nucleic acid sequence targeted by the assay.
View the arithmetic average of the technical replicate Cq values.
Applied Biosystems™ Relative Quantitation Analysis Module
59
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Chapter 8 Screens and plots
Melt Curve Plot
Column
Adjusted CT/ CRT
Mean
Use this column to...
View the average of the technical replicate Cq values that have been adjusted based on the
"Maximum allowed CT" limit defined in the RQ Settings analysis settings.
Note: Wells with Cq scores greater than the "Maximum allowed CT" value are adjusted to the
specified Cq limit.
View the arithmetic average of the technical replicate ∆Cq values for the sample replicate
group.
∆CT/∆CRT Mean
Note: The ∆CT/∆CRT mean is calculated at the reaction plate level and represents the mean
difference between the target ∆CT/∆CRT values and the endogenous control ∆CT/∆CRT values
for all the technical replicates for that sample that are present on the plate.
View the sample standard deviation of the sample replicate group level Cq values.
∆CT/∆CRT SE
∆CT/∆CRT + Control
Median
Note: The ∆CT/∆CRT SE value is calculated differently for multiplex and singleplex
experiments. For multiplex experiments, the calculation is at the well level. For singleplex
experiments, the calculation combines the plate-level Cq value variation between the target
and the endogenous control.
View the arithmetic average of the technical replicate ∆CT/∆CRT values for the sample
replicate group added to the control median.
Melt Curve Plot
The melt curve plot (also called a dissociation curve plot) displays data collected
during a melt curve stage. Peaks in the melt curve can indicate the melting
temperature (Tm) of a target or can identify nonspecific PCR amplification. The
software displays the melt curve plot only for those experiments with a PCR method
that includes a melt curve stage (a gradual temperature ramp configured for data
collection).
Two views are available:
• Normalized reporter (Rn) vs. temperature — The normalized reporter view
visualizes the rise in fluorescence throughout the temperature ramp. The
normalized reporter (Rn), displayed on the y-axis, is calculated as the
fluorescence signal from the reporter dye normalized to the fluorescence signal of
the passive reference.
• Derivative reporter (−Rn′) vs. temperature — The derivative reporter view
allows you to visualize the maximum rate of change in fluorescence during the
temperature ramp. The derivative reporter, displayed on the y-axis, is calculated
as the negative first derivative of the normalized fluorescence (Rn) generated by
the reporter during PCR amplification.
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Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 8 Screens and plots
Multicomponent Plot
8
Multicomponent Plot
The Multicomponent Plot is a plot of the complete spectral contribution of each dye
for the selected well(s) over the duration of the PCR run.
2
1
3
4
1
Toolbar – Contains the following tools for controlling the
plot:
– Select individual data points from the plot.
– Allows you to click and manually move the position
of the plot.
– Zoom the plot to the selected area.
– Zooms out the plot to show all data points.
– Saves the plot as an image (.png or .jpg).
– Allows you to adjust the display options for the plot.
Target/Sample drop-down list – Selects the data from the
target or sample data displayed by the plot.
3 Normalized fluorescence – Displays the normalized
fluorescence for all wells throughout the duration of the
thermal cycling protocol.
4 Legend – Fluorescent dyes present in the analyzed data.
2
When you analyze your own experiment, confirm the following:
• The passive reference dye fluorescence level should remain relatively constant
throughout the PCR process.
• The reporter dye fluorescence level should display a flat region corresponding to
the baseline, followed by a rapid rise in fluorescence as the amplification
proceeds.
• There should not be any spikes, dips, and/or sudden changes in the fluorescent
signal.
• There should not be any amplification in negative control wells.
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Chapter 8 Screens and plots
Outlier Wheel Plot
Outlier Wheel Plot
The Outlier Wheel is a data review tool that can greatly simplify the quality control
review of very large data sets, especially data generated by OpenArray experiments.
When a sample, target, or plate data set consists of thousands of data points, you can
use the Outlier Wheel to organize and review the data set for irregular amplification.
The Outlier Wheel simplifies the review process by visualizing the amplification data
of a given data set in a circular format, where each amplification curve in the set is
represented as a colored line extending from a central axis. As shown in the following
figure, each line is broken into colored segments that map to regions of the
amplification curve, where:
• Segment length indicates the increase in normalized fluorescence (Rn) at a given
PCR cycle.
• Segment color indicates the PCR cycle number at which signal was collected.
In the example below, the amplification curve exhibits little growth in Rn during cycle
1 (shown in cyan). Therefore, the projection of that section of the curve on the Rn scale
translates into a small segment (cyan) in the corresponding line on the Outlier Wheel.
In contrast, the amplification curve exhibits a large increase in Rn during cycle 5
(shown in light green) that translates into a much larger line segment (light green) in
the corresponding line.
30
25
20
15
Rn
10
5
0
1
2
3
4
5
6
7
8
9
10
Cycle number
The combination of line segment color and length for each data point in the Outlier
Wheel allows you to understand the shape of the related amplification curve and
where most amplification occurs during the PCR. For example, reactions that amplify
during the early cycles of the PCR appear primarily blue or green (early cycle colors),
whereas reactions that amplify later appear primarily orange or red (later cycle
colors), because those respective colors represent the cycles during which the
maximum increase in Rn occurs.
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Chapter 8 Screens and plots
RQ Plot
8
RQ Plot
The RQ (Relative Quantitation) Plot displays the results of the relative quantitation
calculations in the gene expression profile. Three plots are available:
• RQ vs Target – Groups the relative quantitation (RQ) values by target. Each
sample is plotted for each target. You can view the plot as the following graph
types: linear, log10, Ln, log2.
• RQ vs Sample (present when the plot displays results by Samples) – Groups the
relative quantitation (RQ) values by sample. Each target is plotted for each
sample. You can view the plot as the following graph types: linear, log10, Ln,
log2.
• RQ vs BioGroup – (present when the plot displays results by Biogroups) –
Groups the relative quantitation (RQ) values by biological replicate group. Each
target is plotted for each sample. You can view the plot as the following graph
types: linear, log10, Ln, log2.
IMPORTANT! If one or more assay efficiencies are set less than 100%, then the
Applied Biosystems™ Software performs the gene expression calculation using
equivalent Cq values, where the software adjusts the Cqs of each target proportionally
to achieve equivalent efficiency. The resulting equivalent Cqs calculated for the
affected targets reflect the values expected if the assays performed at 100% efficiency.
Below the gene expression plot is the Results Details table, showing the following
information:
Column
Use this column to...
Target
View the ID (a unique name or number) of the nucleic acid sequence targeted by the assay.
Sample
View the ID (a unique name or number) of the sample.
Biological Group
Max CT/CRT
CT/CRT Mean
Adjusted CT/CRT Mean
CT/CRT SE
View the biological group (a unique name or number) to which the sample belongs.
View the maximum Cq defined by the "Maximum allowed CT" limit in the RQ Settings analysis
settings.
View the arithmetic average of the technical replicate Cq values.
View the average of the technical replicate Cq values that have been adjusted based on the
"Maximum allowed CT" limit defined in the RQ Settings analysis settings.
Note: Wells with Cq scores greater than the "Maximum allowed CT" value are adjusted to the
specified Cq limit.
View the sample standard deviation of the sample replicate group level Cq values.
View the arithmetic average of the technical replicate Cq values for the sample replicate
group.
∆CT/∆CRT Mean
Note: The ∆CT/∆CRT mean is calculated at the reaction plate level and represents the mean
difference between the target Cq values and the endogenous control Cq values for all the
technical replicates for that sample that are present on the plate.
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Chapter 8 Screens and plots
RQ Plot
Column
Use this column to...
View the sample standard deviation of the sample replicate group level Cq values.
∆CT/∆CRT SE
F-Factor
View the calculated F-Factor for the replicate group associated with the reference sample.
∆∆CT/∆∆CRT
View the calculated ΔΔCT value for the replicate group associated with the reference sample.
∆∆CT/∆∆CRT ± FSigma
View the calculated ΔΔCT value added to or subtracted from the F-Sigma value calculated for
the replicate group associated with the reference sample.
RQ
View the calculated relative level of gene expression for the replicate group that is associated
with the test sample.
RQ Min
RQ Max
64
Note: The ∆CT/∆CRT SE value is calculated differently for multiplex and singleplex
experiments. For multiplex experiments, the calculation is at the well level. For singleplex
experiments, the calculation combines the plate-level Cq value variation between the target
and the endogenous control.
View the minimum relative level of gene expression in the test samples calculated using the
confidence level set in the analysis settings.
Note: The minimum includes the variability associated with the endogenous control and
targets in only the test samples.
View the maximum relative level of gene expression in the test samples calculated using the
confidence level set in the analysis settings.
Note: The maximum includes the variability associated with the endogenous control and
targets in only the test samples.
Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 8 Screens and plots
Volcano Plot
8
Volcano Plot
The volcano plot displays the p-value versus the fold change for each target in a
biological group, relative to the reference group. Green and red dots represent targets
with a fold change outside (greater or lesser than) the fold change boundary. Compare
the size of the fold change (x-axis) to the statistical significance level (y-axis) on the
volcano plot.
Note: You must have biological groups assigned (so that p-values can be calculated)
before you can view data on the volcano plot.
IMPORTANT! If one or more assay efficiencies are set to <100%, then the Applied
Biosystems™ Software performs the gene expression calculation using equivalent Cq
values, where the software adjusts the Cqs of each target proportionally to achieve
equivalent efficiency. The resulting equivalent Cqs calculated for the affected targets
reflect the values expected if the assays performed at 100% efficiency.
Below the plot is the Results Details table, showing the following information:
Column
Biological Group
Target
CT/CRT Mean
Adjusted CT/CRT Mean
Use this column to...
View the biological group (a unique name or number) to which the sample belongs.
View the ID (a unique name or number) of the nucleic acid sequence targeted by the assay.
View the arithmetic average of the technical replicate Cq values.
View the average of the technical replicate Cq values that have been adjusted based on the
"Maximum allowed CT" limit defined in the RQ Settings analysis settings.
Note: Wells with Cq scores greater than the "Maximum allowed CT" value are adjusted to the
specified Cq limit.
View the arithmetic average of the technical replicate Cq values for the sample replicate
group.
∆CT/∆CRT Mean
Note: The ∆CT/∆CRT mean is calculated at the reaction plate level and represents the mean
difference between the target Cq values and the endogenous control Cq values for all the
technical replicates for that sample that are present on the plate.
View the sample standard deviation of the sample replicate group level Cq values.
∆CT/∆CRT SE
Note: The ∆CT/∆CRT SE value is calculated differently for multiplex and singleplex
experiments. For multiplex experiments, the calculation is at the well level. For singleplex
experiments, the calculation combines the plate-level Cq value variation between the target
and the endogenous control.
∆∆CT/∆∆CRT
View the calculated ΔΔCT value for the replicate group associated with the reference sample.
RQ
View the calculated relative level of gene expression for the replicate group that is associated
with the test sample.
RQ Min
View the minimum relative level of gene expression in the test samples calculated using the
confidence level set in the analysis settings.
Note: The minimum includes the variability associated with the endogenous control and
targets in only the test samples.
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Chapter 8 Screens and plots
Well Table
Column
RQ Max
Use this column to...
View the maximum relative level of gene expression in the test samples calculated using the
confidence level set in the analysis settings.
Note: The maximum includes the variability associated with the endogenous control and
targets in only the test samples.
P-Value
View the probability (P-value) that the observed RQ (fold change) in gene expression for the
replicate group associated with the test sample is not differentially expressed due to
treatment or condition.
Result
View the assignment for the replicate group that is associated with the test sample, where
possible states are: down-regulated, up-regulated, insignificant, or flat.
Well Table
The Well Table summarizes the analyzed data for a single experiment from the
project. To view the Well Table, select Quality Control & Results, select an
experiment of interest, then select Well Table from the View By drop-down list.
You can organize the contents of the well table as follows:
• Use the "Group By" table setting to group the data displayed within the table by
sample, plate, or task. When grouped, select rows to evaluate subsets of the
amplification data in the plot, which can be useful when reviewing amplification
across replicate wells.
• Click a table column heading to sort the contents (or click
in the header, then
select
or ). The presence of an arrow ( or ) in the column header
indicates the direction of the sort.
• Click
in a column header, then click
and select a parameter to filter the
contents. When filtered, click Clear to remove the filter from the table.
• Click
in any column header, then click
want to show or hide.
and select the columns that you
• Click
in a column header, then click
(or ) to lock (or unlock) the horizontal
position of the column within the table. When a column is unlocked, you can
click and drag the column header to reposition the column within the table.
Table 1 Box Plot Well Table
Column
Sample
Biological Group
Mean
66
Definition
The ID (a unique name or number) of the sample.
The biological group (a unique name or number) to which the sample belongs.
The arithmetic average of the technical replicate CT values.
Min
The minimum technical replicate CT value for the test sample calculated using the
confidence level set in the analysis settings.
Max
The maximum technical replicate CT value for the test sample calculated using the
confidence level set in the analysis settings.
Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 8 Screens and plots
Well Table
Column
Median
Q1
Q3
8
Definition
The median CT value for the technical replicates of the sample.
The 1st Quartile (Q1) for the sample replicate group, which is calculated as the numeric
midpoint between the lowest and median CT values of the technical replicates.
Note: The 1st Quartile defines lower boundary of the inter-quartile region (IQR), which is
defined as the difference between the 3rd and 1st quartile.
The 3rd Quartile (Q3) for the sample replicate group, which is calculated as the numeric
midpoint between the median and maximum CT values of the technical replicates.
Table 2 Relative Quantitation Plot Well Table
Column
Definition
Target
The ID (a unique name or number) of the nucleic acid sequence targeted by the assay.
Sample
The ID (a unique name or number) of the sample.
Biological Group
Max CT/CRT
CT/CRT Mean
Adjusted CT/CRT Mean
CT/CRT SE
The biological group (a unique name or number) to which the sample belongs.
The maximum Cq defined by the "Maximum allowed CT" limit in the RQ Settings analysis
settings.
The arithmetic average of the technical replicate Cq values.
The average of the technical replicate Cq values that have been adjusted based on the
"Maximum allowed CT" limit defined in the RQ Settings analysis settings.
Note: Wells with Cq scores greater than the "Maximum allowed CT" value are adjusted to the
specified Cq limit.
The sample standard deviation of the sample replicate group level Cq values.
The arithmetic average of the technical replicate Cq values for the sample replicate group.
∆CT/∆CRT Mean
Note: The ∆CT/∆CRT mean is calculated at the reaction plate level and represents the mean
difference between the target Cq values and the endogenous control Cq values for all the
technical replicates for that sample that are present on the plate.
The sample standard deviation of the sample replicate group level Cq values.
∆CT/∆CRT SE
Note: The ∆CT/∆CRT SE value is calculated differently for multiplex and singleplex
experiments. For multiplex experiments, the calculation is at the well level. For singleplex
experiments, the calculation combines the plate-level Cq value variation between the target
and the endogenous control.
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Chapter 8 Screens and plots
Well Table
Column
Definition
The calculated F-Factor for the replicate group associated with the reference sample.
The F-Factor is used to calculate the RQ confidence intervals in the ∆∆CT calculation
(displayed as error bars in the RQ plot). The value is calculated differently depending on the
RQ Settings in the analysis settings for your project.
F-Factor
• If you specified a Confidence level setting, then the F-Factor is the t-value of the
Student's t-distribution calculated from the:
– Degrees of freedom that characterize the distribution of the replicate population. If
the project contains no biological groups, degrees of freedom is calculated per
Technical Test Sample as:
#Technical Replicates WellsTarget + #Technical Replicates WellsEndo - 2.
Otherwise, the value is calculated per Biological Test Sample as:
#Technical Replicates Groups Test Sample - 1.
– Probability associated with the two-tailed Student's t-distribution (determined by
the RQ Settings in the analysis settings for your project).
• If you specified a Limit by standard deviations setting, then the F-Factor is equal to the
setting (1, 2, or 3).
∆∆CT/∆∆CRT
∆∆CT/∆∆CRT ± FSigma
The calculated ΔΔCT value added to or subtracted from the F-Sigma value calculated for the
replicate group associated with the reference sample.
RQ
The calculated relative level of gene expression for the replicate group that is associated with
the test sample.
RQ Min
RQ Max
68
The calculated ΔΔCT value for the replicate group associated with the reference sample.
The minimum relative level of gene expression in the test samples calculated using the
confidence level set in the analysis settings.
Note: The minimum includes the variability associated with the endogenous control and
targets in only the test samples.
The maximum relative level of gene expression in the test samples calculated using the
confidence level set in the analysis settings.
Note: The maximum includes the variability associated with the endogenous control and
targets in only the test samples.
Applied Biosystems™ Relative Quantitation Analysis Module
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Quality flags
■
■
■
■
■
■
■
■
■
■
■
■
■
■
■
■
■
■
■
■
■
■
■
■
■
AMPNC (Amplification in negative control) quality flag . . . . . . . . . . . . . . . . . . . 70
AMPSCORE (Low signal in linear phase) quality flag . . . . . . . . . . . . . . . . . . . . . 70
BADROX (Bad passive reference signal) quality flag . . . . . . . . . . . . . . . . . . . . . . 71
BLFAIL (Baseline algorithm failed) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
CQCONF (Calculated confidence in the Cq value is low) quality flag . . . . . . . . 72
CRTAMPLITUDE (Broad Cq Amplitude) quality flag . . . . . . . . . . . . . . . . . . . . . 72
CRTNOISE (Cq Noise) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
CTFAIL (Cq algorithm failed) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
DRNMIN (Detection of minimum DRn due to abnormal baseline)
quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
EXPFAIL (Exponential algorithm failed) quality flag . . . . . . . . . . . . . . . . . . . . . . 73
HIGHSD (High standard deviation in replicate group) quality flag . . . . . . . . . . 74
LOWROX (Low ROX™ Intensity) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
MAXCT (Cq above maximum) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
MPOUTLIER (ΔCq outlier in multiplex experiment) quality flag . . . . . . . . . . . . 75
MTP (Melt curve analysis shows more than one peak) quality flag . . . . . . . . . . 75
NOAMP (No amplification) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
NOISE (Noise higher than others in plate) quality flag . . . . . . . . . . . . . . . . . . . . 76
NOSAMPLE (No sample assigned to well) quality flag . . . . . . . . . . . . . . . . . . . . 77
NOSIGNAL (No signal in well) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
OFFSCALE (Fluorescence is offscale) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . 78
OUTLIERRG (Outlier in replicate group) quality flag . . . . . . . . . . . . . . . . . . . . . 79
PRFDROP (Passive reference signal changes significantly near the
Cq/Ct) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
PRFLOW (Average passive reference signal is below the threshold)
quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
SPIKE (Noise spikes) quality flag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
THOLDFAIL (Thresholding algorithm failed) quality flag . . . . . . . . . . . . . . . . . 81
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Chapter 9 Quality flags
AMPNC (Amplification in negative control) quality flag
AMPNC (Amplification in negative control) quality flag
The AMPNC (
amplified.
) quality flag indicates that a sequence in a negative control reaction
If a well is flagged, confirm the results:
1. Select the flagged well(s) in the plate layout or well table.
2. Make sure that the well corresponds to a negative control well (Task = Negative
Control or NTC).
3. View the amplification plot [∆Rn vs. Cycle (Linear) or ∆Rn vs. Cycle (Log)], and
confirm the fluorescence signal increased for the flagged negative control well. If
the fluorescence signal did not increase, omit the well from analysis.
Possible Cause
Contamination in one or
more PCR reaction
components
Recommended Action
• Replace all PCR reaction components with new
components, then repeat the experiment. Make sure
to add water or buffer instead of sample to the well.
• Decontaminate the work area and pipettors.
Unstable reaction mix
• Use a hot-start enzyme.
• If you are not using a hot-start enzyme, run the
reactions as soon as possible after you prepare them.
Poor primer and/or probe
design
Redesign the primers and/or probe.
AMPSCORE (Low signal in linear phase) quality flag
The AMPSCORE ( ) quality flag indicates that, for a given well, the amplification in
the linear region is below a certain threshold, corresponding to the score set in the
analysis settings.
Use the AMPSCORE flag to easily identify and, optionally, omit potentially poor
results without manually inspecting every amplification curve. The numeric value for
the amplification score is found in the Amp Score column of the well table for the
amplification and multicomponent plots.
Note: For Quantitative or Genotyping applications, this flag is only appropriate when
ROX™ dye is used as the passive reference or the data is from OpenArray™ plates. For
Absolute Quantification applications, this flag is only appropriate when ROX™ dye is
used as the passive reference.
If a well is flagged, confirm the results:
1. Select the flagged well(s) in the plate layout or well table.
2. Make sure that the well does not correspond to a negative-control (NTC) well.
3. View the amplification plot [DRn vs. Cycle (Linear) or DRn vs. Cycle (Log)], and
check the shape of the curve. If the curve is atypical, consider omitting the
flagged well(s) from analysis.
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Chapter 9 Quality flags
BADROX (Bad passive reference signal) quality flag
9
BADROX (Bad passive reference signal) quality flag
The BADROX ( ) quality flag indicates that the passive reference (usually ROX™
dye) signal is abnormal. The passive reference signal may not be acceptable for
normalization of the reporter dye signal.
If a well is flagged, confirm the results:
1. Select the flagged well(s) in the plate layout or well table.
2. View the multicomponent plot, and review the passive reference signal for
abnormalities.
3. View the amplification plot [DRn vs. Cycle (Linear) or DRn vs. Cycle (Log)], and
review the data in the Cq region for abnormalities.
4. Examine the reaction plate, and check for condensation and/or inconsistent
reaction volumes.
Possible Cause
Droplets on the sides of the
wells.
Evaporation resulting from
improper sealing or seal
leaks.
Condensation on the
reaction plate.
Recommended Action
Repeat the experiment, and make sure you centrifuge the
plate briefly before loading it into the instrument.
Repeat the reactions, and make sure you seal the plate
properly.
Inconsistent volumes across Confirm that pipettes are calibrated and functioning
the plate.
properly.
Incorrect concentration of
reference dye.
Confirm that you are using the appropriate master mix for
your instrument.
Pipetting errors.
Calibrate your pipettors, then repeat the experiment.
BLFAIL (Baseline algorithm failed) quality flag
Note: The BLFAIL flag is only valid when you use the Baseline Threshold algorithm
to analyze your experiments, though it is always shown in the QC Summary.
The BLFAIL ( ) quality flag indicates that the automatic baseline algorithm failed,
and the software cannot calculate the best-fit baseline for the data.
If a well is flagged, confirm the results:
1. Select the flagged well(s) in the plate layout or well table.
2. View the amplification plot [DRn vs. Cycle (Linear) or DRn vs. Cycle (Log)], and
check for late amplification or no amplification.
3. If the amplification looks acceptable, set the baseline manually.
4. Click Analyze to reanalyze the data.
5. Evaluate the results and, if needed, make any additional changes to the baseline.
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Chapter 9 Quality flags
CQCONF (Calculated confidence in the Cq value is low) quality flag
CQCONF (Calculated confidence in the Cq value is low) quality flag
The CQCONF ( ) quality flag indicates that the calculated confidence for the Cq/CT
value of the well is less than the minimum value defined in the analysis settings.
Use the CQCONF flag to easily identify and, optionally, omit potentially poor results
without manually inspecting every amplification curve. The minimum limit is set in
the Flag Settings tab of the Analysis Settings dialog box.
If a well is flagged, confirm the results:
1. Select the flagged well(s) in the plate layout or well table.
2. View the amplification plot [DRn vs. Cycle (Linear) or DRn vs. Cycle (Log)], and
check the shape of the curve. If the curve is atypical, consider omitting the
flagged well(s) from analysis.
CRTAMPLITUDE (Broad Cq Amplitude) quality flag
The CRTAMPLITUDE ( ) quality flag indicates that the amplitude of the relative
standard curve, generated from the data set that includes the given well, is
significantly lower than the other curves generated for the related target.
CRTNOISE (Cq Noise) quality flag
The CRTNOISE quality flag indicates that for the relative standard curve, generated
from the data set that includes the given well, exhibited a significant amount of
unexplained variability in comparison to the other curves generated for the related
target.
CTFAIL (Cq algorithm failed) quality flag
Note: The CTFAIL flag is only valid when you use the Baseline Threshold algorithm
to analyze your experiments, though it is always shown in the QC Summary.
The CTFAIL ( ) quality flag indicates that the automatic Cq algorithm failed for the
given well, and the software cannot calculate the threshold cycle (Cq).
If a well is flagged, confirm the results:
1. Select the flagged well(s) in the plate layout or well table.
2. View the amplification plot [DRn vs. Cycle (Linear) or DRn vs. Cycle (Log)] and
check for:
• Amplification too early
• Amplification too late
• Low amplification
• No amplification
3. If the amplification looks acceptable, set the threshold and baseline manually.
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Chapter 9 Quality flags
DRNMIN (Detection of minimum DRn due to abnormal baseline) quality flag
9
4. Click Analyze to reanalyze the data.
5. Evaluate the results. If the adjustments do not produce a valid Cq, consider
omitting the well from analysis.
DRNMIN (Detection of minimum DRn due to abnormal baseline)
quality flag
The DRNMIN ( ) quality flag indicates that the normalized fluorescence (DRn) for a
given well dropped below the threshold defined in the analysis settings.
Use the DRNMIN flag to easily identify and, optionally, omit potentially poor results
without manually inspecting every amplification curve. The DRn threshold value is
set in the Flag Settings tab of the Analysis Settings dialog box.
If a well is flagged, confirm the results:
1. Select the flagged well(s) in the plate layout or well table.
2. View the amplification and multicomponent plots [DRn vs. Cycle (Linear) or DRn
vs. Cycle (Log)], and check the shape of the curve. If the curve is atypical,
consider omitting the flagged well(s) from analysis.
EXPFAIL (Exponential algorithm failed) quality flag
Note: The EXPFAIL flag is only valid when you use the Baseline Threshold algorithm
to analyze your experiments, though it is always shown in the QC Summary.
The EXPFAIL ( ) quality flag indicates that the automatic Cq algorithm failed for the
given well, and the software cannot identify the exponential region of the
amplification plot.
If a well is flagged, confirm the results:
1. Select the flagged well(s) in the plate layout or well table.
2. View the amplification plot [ DRn vs. Cycle (Linear) or DRn vs. Cycle (Log)], and
check for:
• Amplification too early
• Amplification too late
• Low amplification
• No amplification
3. If the amplification looks acceptable, set the threshold manually:
a. Click the threshold (the horizontal line across the plot) and drag it up or
down to a location within the exponential region of the amplification.
b. Click Analyze to reanalyze the data.
c. Evaluate the results and, if needed, make any additional changes to the
threshold.
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Chapter 9 Quality flags
HIGHSD (High standard deviation in replicate group) quality flag
HIGHSD (High standard deviation in replicate group) quality flag
The HIGHSD ( ) quality flag indicates that the Cq standard deviation for the
replicate group exceeds the current flag setting (all replicates in the group are
flagged).
If a replicate group is flagged, confirm the results:
1. Select the flagged replicate group in the plate layout or well table.
2. View the amplification plot [DRn vs. Cycle (Linear) or DRn vs. Cycle (Log)], and
evaluate whether the signal varies significantly from others in the replicate
group. If so, omit the outlier well(s) or omit the entire replicate group from
analysis.
3. Only for experiments analyzed with the Baseline Threshold algorithm, if the
amplification looks acceptable, set the threshold manually and reanalyze the
data:
a. Click the threshold (the horizontal line across the plot) and drag it up or
down to a location within the exponential region of the amplification.
b. Click Analyze to reanalyze the data.
c. Evaluate the results, and if needed, make any additional changes to the
threshold.
Possible Cause
Droplets on the sides of the
wells.
Recommended Action
Repeat the experiment, and make sure you centrifuge the
plate briefly before loading it into the instrument.
Improper sealing or seal
leaks.
Condensation on the
reaction plate.
Repeat the reactions, and make sure you seal the plate
properly.
Inconsistent volumes across
the plate.
Pipetting errors.
Calibrate your pipettors, then repeat the experiment.
Repeat the experiment, and make sure to include all
Missing reaction component. reaction components. Try not to pipet less than 5 µL of
sample when setting up the PCR.
74
Incorrect reaction setup.
Make sure you follow the manufacturer's instructions for
setting up the reactions.
Poor DNA template.
Repeat the experiment with higher quality template.
Inadequate mixing
Mix the reaction thoroughly by pipetting or using a medium
setting on a vortex mixer.
Applied Biosystems™ Relative Quantitation Analysis Module
Chapter 9 Quality flags
LOWROX (Low ROX™ Intensity) quality flag
9
LOWROX (Low ROX™ Intensity) quality flag
A Low ROX™ Intensity ( ) quality flag can be raised for any data point. If the ROX™
dye intensity determined by the software for a data point is below the threshold, a
flag will be raised.
If a well is flagged, no action should be taken for the data point. If the ROX™ dye
intensity is below the default threshold, the data point does not meet the minimum
conditions for assigning a call.
MAXCT (Cq above maximum) quality flag
The MAXCT ( ) quality flag indicates that the mean Cq for the replicate group is
above the maximum allowed value.
The maximum allowed value is set in the Flag Settings tab of the Analysis Settings
dialog box. If the mean Cq of the replicate group is above the maximum, the software
adjusts it to the maximum allowed value (shown in the Adjusted Cq column in the
well table).
MPOUTLIER (ΔCq outlier in multiplex experiment) quality flag
The MPOUTLIER quality flag indicates that the ΔCT for the targets in the well is less
than the current flag setting.
If a replicate group is flagged, confirm the results:
1. Select the flagged well(s) in the plate layout or well table.
2. View the amplification plot [ΔRn vs. Cycle (Linear) or ΔRn vs. Cycle (Log)] for
both targets in the well, and make sure that they both amplified.
3. Only for experiments analyzed with the Baseline Threshold algorithm, set the
baseline and threshold values manually.
4. Click Analyze to reanalyze the project.
5. Evaluate the results. If the adjustments do not produce a valid Cq, consider
omitting the well from analysis.
MTP (Melt curve analysis shows more than one peak) quality flag
The MTP ( ) quality flag indicates that the melt curve generated from the collected
data exhibits multiple peaks, indicating possible PCR irregularities such as
contamination or nonspecific amplification.
Note: The MTP flag is present only in experiments with PCR methods that include a
melting curve stage (a temperature ramp configured for data collection).
If a replicate group is flagged, confirm the results in the Melt Curve Plot. Peaks in the
melt curve can indicate the melting temperature (Tm) of a target nucleic acid or
nonspecific PCR amplification.
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Chapter 9 Quality flags
NOAMP (No amplification) quality flag
NOAMP (No amplification) quality flag
The NOAMP (
) quality flag indicates that the sample did not amplify.
If a well is flagged, confirm the results:
1. Select the flagged well(s) in the plate layout or well table.
2. Make sure that the well does not correspond to a negative-control well.
3. View the amplification plot [DRn vs. Cycle (Linear) or DRn vs. Cycle (Log)], and
make sure that the fluorescence signal did not increase in the well.
4. View the multicomponent plot, and look for fluorescence signal higher than the
background.
Possible Cause
Missing template.
Recommended Action
Repeat the experiment, and make sure to include all
reaction components.
• If this occurs in just one sample, it may be correct.
Target is not expressed in
the sample.
• If this occurs in all samples of a particular tissue,
search the literature for evidence that the target is
expressed in the tissue or sample type of interest.
NOISE (Noise higher than others in plate) quality flag
The NOISE ( ) quality flag indicates that the well produced more noise in the
amplification plot than the other wells on the same plate.
If a well is flagged, confirm the results:
1. Select the flagged well(s) and some unflagged unknown wells in the plate layout
or well table.
2. View the amplification plot [DRn vs. Cycle (Linear) or DRn vs. Cycle (Log)] and
check for a noisy amplification curve in the flagged wells.
3. In the multicomponent plot:
a. From the Color by drop-down list, select Dye to color the data according to
the dye.
b. Check for a drop in ROX™ signal relative to the reporter dye and compare
flagged wells with unflagged wells.
c. If there is a drop in the ROX™ signal compared to the reporter dye, consider
omitting the flagged well(s) from analysis.
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Chapter 9 Quality flags
NOSAMPLE (No sample assigned to well) quality flag
9
NOSAMPLE (No sample assigned to well) quality flag
The NOSAMPLE (
) quality flag indicates that no sample is assigned to the well.
In the Applied Biosystems™ Analysis Software, omit the well missing the sample, then
click Analyze to reanalyze the project.
NOSIGNAL (No signal in well) quality flag
The NOSIGNAL ( ) quality flag indicates that the well produced very low or no
fluorescence signal.
If a well is flagged, confirm the results:
1. Select the flagged well(s) and a few unflagged wells in the plate layout or well
table.
2. View the multicomponent plot and compare the flagged well(s) to the unflagged
wells:
• If the fluorescence signals for all dyes are low and similar to the instrument's
background signal, the well is empty.
• If the fluorescence signals are higher than the instrument's background
signal and constant throughout the instrument run, no amplification
occurred.
3. If the flagged well produced no fluorescence signal, omit the well from analysis.
4. If you still have the plate that was run, note the location for each flagged well,
and check each corresponding well in the reaction plate for low reaction volume.
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Chapter 9 Quality flags
OFFSCALE (Fluorescence is offscale) quality flag
OFFSCALE (Fluorescence is offscale) quality flag
The OFFSCALE ( ) quality flag indicates that the fluorescence signal for one or more
dyes in the well exceeds the instrument's maximum detectable range for one or more
cycles.
Confirm the results:
1. Select the flagged well(s) in the plate layout or well table.
2. View the amplification plot [DRn vs. Cycle (Linear) or DRn vs. Cycle (Log)] or the
well table, and note the threshold cycle.
3. View the multicomponent plot, and review the data for a plateau over one or
more cycles. A plateau indicates saturation of the instrument's detectors. If the
signal plateaus before the threshold cycle, omit the well(s).
Possible Cause
Recommended Action
Too much TaqMan® probe or Reduce the concentration of reagent added to the reaction.
SYBR™ Green dye added to
the reaction.
Fluorescent contaminant on Perform a background calibration. If you detect fluorescent
the reaction plate, sample
contamination, clean the block.
block, or adhesive cover.
Fluorescent contaminant in
the reaction.
78
Replace the reagents.
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Chapter 9 Quality flags
OUTLIERRG (Outlier in replicate group) quality flag
9
OUTLIERRG (Outlier in replicate group) quality flag
The OUTLIERRG ( ) quality flag indicates that the Cq for the well deviates
significantly from values in the associated replicate group (only the outlier is flagged).
Outlier removal is based on a modified Grubb's test. For a well to be considered an
outlier, it must be identified as an outlier by Grubb's test and its Cq value must be a
minimum of 0.25 cycles from the mean.
If a well is flagged, confirm the results:
1. Select the flagged well(s) and the associated replicate group in the plate layout or
well table.
2. View the amplification plot [∆Rn vs. Cycle (Linear) or ∆Rn vs. Cycle (Log)], and
compare the data from the flagged well to the data from the unflagged replicates.
If the Cq or the amplification curve for the flagged well vary significantly,
carefully consider omitting the flagged well from analysis.
Possible Cause
Pipetting errors.
Recommended Action
Repeat the reactions, and follow these guidelines to reduce
pipetting errors:
• Prepare enough master reaction mix for the entire
replicate group, then transfer aliquots to all
appropriate wells in the reaction plate.
• Calibrate and service your pipettors regularly.
• Pipette larger volumes.
• Reduce the number of pipetting steps.
Contamination in that well.
Decontaminate the work
area and pipettors.
Improper sealing or seal
leaks.
Replace all reagents, then repeat the experiment.
Repeat the reactions, and make sure you seal the reaction
plate properly.
PRFDROP (Passive reference signal changes significantly near the
Cq/Ct) quality flag
The PRFDROP ( ) quality flag indicates that the florescent signal from the passive
reference changes significantly within defined range around the calculated Cq/CT for a
given well.
Use the PRFDROP flag to easily identify and, optionally, omit potentially poor results
without manually inspecting every amplification curve. The limits of the range are
defined by a detection threshold that is set in the Flag Settings tab of the Analysis
Settings dialog box. The flag is triggered when the passive reference signal for a well
changes within the number of cycles (+/-) defined by the setting from the calculated
Cq/CT.
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Chapter 9 Quality flags
PRFLOW (Average passive reference signal is below the threshold) quality flag
If a well is flagged, confirm the results:
1. Select the flagged well(s) in the plate layout or well table.
2. View the amplification plot [DRn vs. Cycle (Linear) or DRn vs. Cycle (Log)], and
check the shape of the curve. If the curve is atypical, consider omitting the
flagged well(s) from analysis.
PRFLOW (Average passive reference signal is below the threshold)
quality flag
The PRFLOW ( ) quality flag indicates that, for the replicate group of a given well,
the average passive reference signal is below the minimum allowed value.
Use the PRFLOW flag to easily identify and, optionally, omit potentially poor results
without manually inspecting every amplification curve. The minimum allowed value
is set in the Flag Settings tab of the Analysis Settings dialog box.
If a well is flagged, confirm the results:
1. Select the flagged well(s) in the plate layout or well table.
2. View the amplification and multicomponent plots [DRn vs. Cycle (Linear) or DRn
vs. Cycle (Log)], and check the shape of the curve. If the curve is atypical,
consider omitting the flagged well(s) from analysis.
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Chapter 9 Quality flags
SPIKE (Noise spikes) quality flag
9
SPIKE (Noise spikes) quality flag
The SPIKE ( ) quality flag indicates that the amplification curve for the given well
contains one or more data points inconsistent with the other points in the curve.
If a well is flagged, confirm the results:
1. Select the flagged well(s) in the plate layout or well table.
2. View the amplification plot [DRn vs. Cycle (Linear) or DRn vs. Cycle (Log)], and
evaluate whether the noise spike adversely affects the baseline or Cq.
3. If the baseline is adversely affected, set the baseline and threshold values
manually.
4. Click Analyze to reanalyze the data.
5. Evaluate the results. If the adjustments do not produce a valid Cq, consider
omitting the well from analysis.
Possible Cause
Recommended Action
Bubbles in the reaction.
Repeat the reactions, and make sure you centrifuge the
plate for 2 minutes at <1500 rpm and confirm that the
liquid in each well of the plate is at the bottom of the well.
Overall low signal for all
dyes in the reaction.
Repeat the reactions, pipetting a larger volume into all
wells.
ROX™ dye not used as
passive reference.
Repeat the reactions, using ROX™ dye as the passive
reference.
Evaporation due to improper Repeat the reactions, and make sure you seal the reaction
sealing or seal leaks.
plate properly.
THOLDFAIL (Thresholding algorithm failed) quality flag
Note: The THOLDFAIL flag is only valid when you use the Baseline Threshold
algorithm to analyze your experiments, though it is always shown in the QC
Summary.
The THOLDFAIL ( ) quality flag indicates that the automatic Cq algorithm failed,
and the software cannot calculate the threshold for the given well.
If a well is flagged, confirm the results:
1. Select the flagged well(s) in the plate layout or well table.
2. View the amplification plot [∆Rn vs. Cycle (Linear) or ∆Rn vs. Cycle (Log)], and
check for:
• Amplification too early
• Amplification too late
• Low amplification
• No amplification for all wells with this target
3. If the amplification looks acceptable, set the baseline and threshold manually.
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Chapter 9 Quality flags
THOLDFAIL (Thresholding algorithm failed) quality flag
4. Click Analyze to reanalyze the data.
5. Evaluate the results and, if needed, make any additional changes to the threshold
or baseline.
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Customer and technical support
Visit thermofisher.com/support for the latest in services and support, including:
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Note: For SDSs for reagents and chemicals from other manufacturers,
contact the manufacturer.
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Glossary
assay information
files
Assay information files are delivered on Information CDs that accompany TaqMan®
assay orders. Each assay information file contains reference information about the
associated order and technical details of all assays in the shipment.
You can import an assay information file into the Applied Biosystems™ Analysis
Software to add supplementary assay information to a project. Assay information files
are available in three formats (.html, .txt, and .xml), but the Applied Biosystems™
Analysis Software supports only .txt and .xml files.
IMPORTANT! The assay information file must include an assay ID (in the Assay ID
column) for each assay listed in the file. The software matches the assay IDs in the
assay information file with the existing assay IDs in the project.
IMPORTANT! When you import an assay information file, information from the file
populates the corresponding columns in the Assays list in the Overview screen. All
data in the Overview screen are replaced for all assays that are identified in the assay
information file. If the assay information file does not contain information for an
assay, the existing data in the Overview screen is unaffected.
amplification
efficiency (EFF%)
Calculation of the efficiency of the PCR amplification in a standard curve experiment.
EFF% is calculated using the slope of the regression line in the standard curve. A
slope close to -3.32 indicates optimal, 100% PCR amplification efficiency. To use
amplification efficiency in a gene expression project:
• On the instrument where you collected the comparative CT (∆∆CT) data that will
be used in the project, run a standard curve experiment to determine the
efficiency.
• In the Applied Biosystems™ Analysis Software, enter the amplification efficiency
in the Efficiency table in the Relative Quantification Settings tab in the Analysis
Settings dialog box.
amplification plot
Display of data collected during the cycling stage of PCR amplification. The
amplification plot can be viewed as:
• Baseline-corrected normalized reporter (∆Rn) vs. cycle
• Normalized reporter (Rn) vs. cycle
analysis group
84
An analysis group is a project setting that allows you to create a profile of the analysis
and quality settings for the analysis of a project. Analysis groups can be applied either
globally to analyze an entire project, or exclusively to a subset of the experiments or
samples added to a project. Later in the analysis, the Applied Biosystems™ Analysis
Software allows you to switch between analysis groups so that you can compare the
effects of changes to the analysis settings on your results.
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assays
A PCR reaction mix that contains primers to amplify a target and a reagent to detect
the amplified target.
automatic
baseline
An analysis setting for the Baseline Threshold algorithm in which the software
identifies the start and end cycles for the baseline in the amplification plot.
automatic
threshold
An analysis setting for the Baseline Threshold algorithm in which the software
calculates the baseline start and end cycles and the threshold in the amplification plot.
The software uses the baseline and threshold to calculate the threshold cycle (Cq).
baseline
In the amplification plot, the baseline is a cycle-to-cycle range that defines background
fluorescence. This range can be set manually on a target-by-target basis, or
automatically, where the software sets the baseline for each individual well.
Baseline
Threshold
algorithm
Expression estimation algorithm (Cq) which subtracts a baseline component and sets a
fluorescent threshold in the exponential region for quantification.
baseline-corrected
normalized
reporter (∆Rn)
In experiments that contain data from real-time PCR, the magnitude of normalized
fluorescence signal generated by the reporter at each cycle during the PCR
amplification. In the ∆Rn vs Cycle amplification plot, ∆Rn is calculated at each cycle
as:
∆Rn (cycle) = Rn (cycle) - Rn (baseline), where Rn = normalized reporter
biological
replicates
Reactions that contain identical components and volumes, but evaluate separate
samples of the same biological source (for example, samples from three different mice
of the same strain, or separate extractions of the same cell line or tissue sample).
When an experiment uses biological replicate groups in a gene expression project, the
values displayed in the Biological Replicates tab are calculated by combining the
results of the separate biological samples and treating this collection as a single
population (that is, as one sample). For Cq computations (normalizing by the
endogenous control) in a singleplex experiment, the software averages technical
replicates. The averages from the technical replicates are then averaged together to
determine the value for that biological replicate.
box plot
Display of the distribution of Cq values in each sample or for each target. For each box
in the plot:
• The solid box shows the range of the middle 50% of the Cq values for the target or
the sample.
• The horizontal black bar shows the median Cq value.
• The black circle shows the mean Cq value.
• The ends of the vertical lines (or "whiskers") show the maximum and minimum
Cq values, unless outliers are present.
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• Mild outliers are displayed as open circles and represent samples or targets with
Cq values up to 1.5X the inter-quartile region (IQR). The IQR is the difference
between the 3rd quartile and the 1st quartile. There is one circle for each Cq in
this range.
• Extreme outliers are displayed as open triangles and represent samples or targets
with Cq values up to 3.0X the IQR. There is one triangle for each Cq in this range.
comparative CT
(∆∆CT) method
Method for determining relative target quantity ("RQ" or fold change) in samples. The
software measures amplification of the target and of the endogenous control in
samples and in a reference sample. Measurements are normalized using the
endogenous control or global normalization. The software determines the RQ (fold
change) of target in each sample by comparing normalized target quantity in each
sample to normalized target quantity in the reference sample.
correlation
coefficient
A measure of the strength of the linear relationship between two variables. The
software calculates the correlation coefficient (r) for either Cq or ∆Cq for all targets in a
pair of samples or a pair of biological groups, for all samples and biological groups in
the study. r can range from -1 to 1.
• If r is close to 0, there is no relationship between the Cq values for the two
samples or groups.
• If r is positive, as the Cq value for one sample (or groups) increases, so does the
other.
• If r is negative, as the Cq value for one sample (or group) increases, the other
decreases (often called an "inverse" correlation).
CRT
See relative threshold cycle (CRT).
CRT algorithm
See Relative Threshold algorithm.
cycle threshold
See threshold cycle (CT).
cycling stage
See threshold cycle (CT).
CT
See threshold cycle (CT).
CT algorithm
See Baseline Threshold algorithm.
delta Rn (∆Rn)
See baseline-corrected normalized reporter (∆Rn).
EFF%
See amplification efficiency (EFF%).
efficiency
correction
A feature in the software that mathematically compensates for differences in
amplification efficiency of the targets and endogenous controls when calculating
relative quantities. The software requires you to enter amplification efficiencies to
perform the correction.
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To use efficiency correction in a gene expression project:
• On the instrument where you collected the comparative CT (∆∆CT) data that will
be used in the project, run a standard curve experiment to determine the
efficiency.
• In Applied Biosystems™ Analysis Software, enter the amplification efficiency in
the Efficiency table in the Relative Quantification Settings tab in the Analysis
Settings dialog box.
endogenous
control
A gene (or genes) used to correct for different amounts of starting material of RNA.
Many genes can be candidates for endogenous controls, but the consistency of
expression in different samples and different treatments should be validated
experimentally.
Global normalization is an alternate normalization method.
For more information about selecting an endogenous control, see the application note
Using TaqMan® Endogenous Control Assays to Select an Endogenous Control for
Experimental Studies (Pub. no. CO16806) available from the Thermo Fisher Scientific
web site.
flag
A quality control (QC) indicator which, when applied by the software to a well during
analysis, indicates a possible issue with that reaction. A summary of the flags
identified in the project is displayed in the Flag Summary screen.
gene expression
plot
Display of RQ versus sample or RQ versus target. RQ for the targets in the reference
sample or group is always 0. The error bars indicate RQ minimum and maximum.
global control
mean
The mean Cq of the endogenous controls for the project. If you are using global
normalization, the global control mean is the median of all values used for global
normalization.
global
normalization
A method to correct for different amounts of starting material of RNA. Global
normalization first finds the assays common to every sample and then uses the
median Cq of those assays as the normalization factor, on a per sample basis. It has
been shown that this type of normalization is only valid if a large number (384 or
greater) of genes are profiled. As an alternative to global normalization, one or more
targets can be selected as the endogenous control.
Global normalization is described in Mestdagh P.,Van Vlierberghe P., De Weer A., et al.
2009. A novel and universal method for microRNA RT-qPCR data normalization.
Genome Biology 10, R64.
heat map
A representation of the level of expression of many targets (genes) across a number of
comparable samples. The targets and samples are clustered according to the similarity
of their gene expression, using unsupervised hierarchical clustering. The color
indicates a change from the mean ΔCT (ΔCRT) value. Red or yellow is an increase,
green or blue is a decrease.
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The "zero" point for the color scale (representing no change in expression) is set
differently for each plot type:
• Global (ΔCT) - The mean ΔCT for all targets in the project.
• Global (ΔCT Plus) - For studies using an endogenous control, the median of all
(ΔCT + the global control mean) values for all targets in the project. For studies
using global normalization, the median of all (ΔCT + the global control median)
values for all targets in the project.
• Target-centric - The median of all ΔCT values for all samples for that target (data
points for a given target can only be compared relative to other data points for
that target).
• Sample-centric - For each sample, the middle expression is set as the mean ΔCT
for all targets in the sample.
manual baseline
An analysis setting for the Baseline Threshold algorithm in which you enter the
baseline start and end cycles for the amplification plot for a target. If you edit the
baseline start and end cycles, the settings are applied to all instances of that target in
the project.
manual threshold
An analysis setting for the Baseline Threshold algorithm in which you enter the
threshold value and select whether to use automatic baseline or manual baseline
values. The software uses the baseline and threshold values to calculate the threshold
cycle (Cq).
multicomponent
plot
A plot of the complete spectral contribution of each dye for the selected well(s) over
the duration of the PCR run.
negative control
(NC)
See no template control (NTC).
no template
control (NTC)
In the software, the task for targets in wells that contain water or buffer instead of
sample. No amplification should occur in negative control wells. Also called negative
control (NC).
nonfluorescent
quencher-minor
groove binder
(NFQ-MGB)
Molecules that are attached to the 3′ end of TaqMan® MGB probes. When the probe is
intact, the nonfluorescent quencher (NFQ) prevents the reporter dye from emitting
fluorescence signal. Because the NFQ does not fluoresce, it produces lower
background signals, resulting in improved precision in quantification. The minor
groove binder moiety (MGB) increases the melting temperature (Tm) without
increasing probe length. It also allows the design of shorter probes.
normalized
quantity
The average Cq of the target gene less the average Cq of the endogenous control(s) or
normalization factor.
normalized
quantity mean
The relative standard curve equivalent of the ∆CT (or ∆CRT) mean value found in
comparative CT experiments (computed as the geometric mean).
normalized
quantity SE
The relative standard curve equivalent of the ∆CT (or ∆CRT) SE value found in
comparative CT experiments (computed as the geometric standard error of the mean).
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normalized
reporter (Rn)
Fluorescence signal from the reporter dye normalized to the fluorescence signal of the
passive reference (usually ROX™ dye).
omit well
An action that you perform before reanalysis to omit one or more wells from analysis.
Because no algorithms are applied to omitted wells, omitted wells contain no results.
You can add wells back in to the analysis; no information is permanently discarded.
outlier
A data point that deviates significantly from the values of an associated group (for
example, the other technical replicates for a sample).
passive reference
A dye that produces fluorescence signal independent of PCR amplification, and that is
added to each reaction at a constant concentration. Because the passive reference
signal should be consistent across all wells, it is used to normalize the reporter dye
signal to account for non-PCR related fluorescence fluctuations caused by minor wellto-well differences in volume. Normalization to the passive reference signal generally
results in data with noticeably high precision among technical replicates.
plate grid (plate
layout)
An illustration of the grid of wells and assigned content in the reaction plate, array
card, or OpenArray™ plate. The number of rows and columns in the grid depends on
the plate or card that you use.
In the software, you can use the plate grid to view well assignments and results. The
plate grid can be printed, included in a report, exported, and saved as a slide for a
presentation.
projects
The Applied Biosystems™ Analysis Software organizes the analysis of experiment
data by project, which represents the association of the raw data, all experimental
setup information, and any associated settings used to perform the analysis. Once
created, projects can be shared with other users and transferred to/from the
repository.
Note: Projects to not contain the data from experiments uploaded to the repository;
they link the data for analysis without affecting the original data files.
p-value
The probability that the observed RQ (fold change) differs from the null hypothesis by
chance. For a gene expression project, the null hypothesis is: the gene is not
differentially expressed due to the treatment or condition. In other words, the p-value
is the probability that RQ ≠1 is not due solely to chance. Traditionally, researchers
reject a hypothesis if the p-value is less than 0.05.
• A low p-value indicates there is evidence against the null hypothesis, and thus
more evidence that the gene is differentially expressed.
• A high p-value indicates little or no evidence against the null hypothesis, thus
less evidence that the gene is differentially expressed.
quantity
In quantification experiments, the amount of target in the samples. Relative quantity
refers to the fold-difference between normalized quantity of target in the sample and
normalized quantity of target in the reference sample.
quencher
A molecule attached to the 3' end of TaqMan® probes to prevent the reporter from
emitting fluorescence signal while the probe is intact. With TaqMan® probes, a
nonfluorescent quencher-minor groove binder (NFQ-MGB) can be used as the
quencher.
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reference sample
In comparative CT (∆∆CT) experiments or gene expression studies, the sample used as
the basis of comparison for relative quantification results. Also called the calibrator.
For a gene expression project using biological groups, a biological group is used as the
reference rather than a sample.
reject well
An action that the software performs during analysis to remove one or more wells
from further analysis if a specific flag is applied to the well. Rejected wells contain
results calculated up to the point of rejection.
Relative Threshold
algorithm
Well-based analysis (CRT) based on the PCR reaction efficiency and fitted to the
amplification curve.
relative threshold
cycle (CRт)
The PCR cycle number for the threshold calculated from the modeled amplification
efficiency profile.
replicates
Identical reactions containing identical components and volumes.
reporter
A fluorescent dye used to detect amplification. With TaqMan® reagents, the reporter
dye is attached to the 5' end. With SYBR™ Green reagents, the reporter dye is SYBR™
Green dye.
Rn
See normalized reporter (Rn).
ROX dye
A dye used as the passive reference.
RQ minimum and
maximum
The relative target quantity (RQ) minimum and maximum and values define the error
associated with the reported RQ value for a target. These values are computed using
confidence or standard deviation:
• Confidence:
– RQmin= 2 -(RQ-SE)
– RQmax= 2 -(RQ+SE)
where SE is the standard error for the RQ.
• Standard deviation:
– RQmin= 2 -(RQ-SD)
– RQmax= 2 -(RQ+SD)
where SD is the standard deviation for the RQ.
run method
The reaction volume and the thermal profile (thermal cycling parameters) for the
instrument run.
sample
The biological tissue or specimen that you are testing for a target gene.
sample design file
A tab-or comma-delimited file (*.txt or *.csv) that contains a list of sample names and
the corresponding name of the biological group to which each sample belongs.
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scatter plot
Display showing the correlation between Cq or ∆CT (Cq or ∆CRT) for targets in a pair
of samples or biological groups. The scatter plot represents Pearson's productmoment correlation coefficient (r) for each target for a pair of samples or biological
groups.
• Targets on or along the line of reference indicate a correlation between the
samples or biological groups.
• Targets that are scattered in the plot, away from the line of reference, indicate
weak or no correlation.
The line of reference is fixed in the software.
score
A measure of the stability of the expression of a candidate or endogenous control
compared to all the other selected candidate or endogenous controls. The score is the
average pairwise variation of the selected candidate or endogenous control compared
to all the other candidate or endogenous control genes. The lower the score, the more
stable the expression of that target relative to all other targets in the comparison.
The score is calculated as follows:
• For control i, calculate ΔCT (or ΔCRT)ij for all samples using another control j as
the normalizer, and calculate the standard deviation (SDij) of the ΔCT (or ΔCRT)ij
values
• Repeat the calculation for all other candidate controls, j = 1…N-1 and use the
average of all SDij's as the stability score for control i.
Note: A minimum of two controls are needed to calculate a score. Because the score
is relative to other controls, when you only have two controls, the score is the same for
both controls.
For more information, see Vandesompele J., De Preter K., Pattyn F., et al. 2002.
Accurate normalization of real-time quantitative RT-PCR data by geometric averaging
of multiple internal control genes. Genome Biology 3, research0034.
signal correlation
plot
Display of the correlation coefficient (r) for every pair of samples or biological groups
in the project. Each cell represents a different scatter plot, colored to indicate the
strength of the correlation.
• Red cells represent a low absolute value for r (|r|), indicating low correlation
(either negative or positive) between samples or groups.
• Green cells represent a high absolute value for r (|r|), indicating high correlation
(either negative or positive) between samples or groups.
target
The nucleic acid sequence to amplify and detect.
target color
In the software, a color assigned to a target to identify the target in the Endogenous
Controls plot and analysis plots.
task
In the software, the type of reaction performed in the well for the target.
Available tasks include:
technical
replicates
Reactions that contain identical components and volumes, and that evaluate the same
sample; important for evaluating precision.
Applied Biosystems™ Relative Quantitation Analysis Module
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thermal profile
The part of the run method that specifies the temperature, time, ramp, number of
cycles, and data collection points for all steps and stages of the instrument run.
threshold
In amplification plots, the threshold is the level of fluorescence above the baseline and
within the exponential amplification region. For the Baseline Threshold algorithm, the
threshold can be determined automatically (see automatic threshold), or it can be set
manually (see manual threshold).
threshold cycle
(CT)
The PCR cycle number at which the fluorescence meets the threshold in the
amplification plot.
unknown
In the software, the task for the target in wells that contain the sample being tested.
For quantification experiments, the unknown task is assigned to wells that contain a
sample with unknown target quantities.
volcano plot
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A display of p-value (biological significance) versus fold change (statistical
significance) for targets in a biological group compared to the reference group. The
plot has boundaries indicating a specified fold change and p-value. Targets with fold
change outside the specified fold change are colored, making it easy to identify
significant changes in gene expression.
Applied Biosystems™ Relative Quantitation Analysis Module
For support visit thermofisher.com/support or email techsupport@lifetech.com
thermofisher.com
31 May 2016
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