| qPCR
Software
Download
page |
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REST -
Relative Expression Software Tool:
Important
Notes !
REST
description:
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Further qPCR software applications:
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Important
note
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The
REST Excel spreadsheet ZIP files are password protected.
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new information about real-time PCR
hardware, software and chemistries.
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REST 2008
version 2.0.7
released 21. June
2008
=> download latest
version - REST 2009
=>
download
=>
Manual REST 2008
=>
short description
of REST-2008 |
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REST
2008 is a standalone software package for
analyzing gene expression using real-time
amplification data. The software addresses
issues surrounding the measurement of
uncertainty in expression ratios by
introducing randomization and bootstrapping
techniques. New confidence intervals for
expression levels also allow measurement of
not only the statistical significance of
deviations but also their likely magnitude,
even in the presence of outliers. Whisker
box plots provide a visual representation of
variation for each gene, highlighting
potential issues such as distribution skew.
REST 2008 builds on its predecessor REST
2005 with significant improvements to
randomization algorithms. This new revision
introduces alternative data inputs such as
single sample efficiency and amplification
take-off point, alleviating the need to set
amplification plot thresholds.
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REST 2005
version 1.9.6 released
November 2005
version
1.9.9 released December
2005
version
1.9.12 released in April 2006
REST 2005 is a new standalone software tool to
estimate up and down-regulation for gene expression
studies. The software addresses issues
surrounding the measurement of uncertainty for
expression ratios, by using
randomisation and bootstrapping techniques. By
increasing the number of iterations from
2,000 to 50,000 in this version hypothesis tests
achieve a level of consistency on par withtraditional
statistical tests. New confidence intervals for
expression levels also allow scientists to measure
not only the statistical significance of deviations,
but also their likely magnitude, even in thepresence
of outliers. Graphical output of the data via a
whisker box-plots provide a visual representation
of variation for each gene that highlights potential
issues such as distribution skew.
=> download latest
version - REST 2009
=> download
=>
Manual REST 2005
=>
Short
description
of REST-2005
REST-384
beta version 2 [ August 2006 ]
New
features
in REST-384:
-> up
to
15 genes can be analysed
-> up to 20 replicated per group
-> more reference genes
can be chosen
-> calculation of an geometric mean of the chosen
RGs => RG Index
-> optimal for high throughput 96- and 384-well
plate qPCR applications
-> efficiency calculation
via dilution row
-> manual efficiency input
-> data output in a graph with error bars
-> error estimation of the
calculated ratio using a Taylor's series
-> bugs removed in randomisation test
Short
description of REST-384
REST-RG
beta
software
version
3 [ August 2006 ]
=> download here: rest-rg-beta-9august2006.zip
New features in REST-RG:
->
up
to 15 genes can be analysed
-> up to 20 replicated per group
-> more reference genes can
be chosen
-> calculation of an geometric mean of the
chosen RGs => RG Index
-> optimal
for
Rotor-Gene
3000
or
Rotor-Gene 6000 applications
->
direct import of Rotor-Gene take off points
(TOP) via copy-and-paste
-> direct
import of single-run qPCR
amplification efficiencies via copy-and-paste
-> manual
efficiency input
-> data output in a graph with error bars
-> error estimation of the
calculated ratio using a Taylor's series
-> bugs removed in randomisation
test
Short description of
REST-RG
REST-MCS
beta
software version 2 [
August 2006 ]
New
features
in REST-MCS:
-> up to 10 genes can
be
analysed
-> up to 10 replicated
per group
-> more reference genes
can be chosen
-> calculation of an geometric mean of
the chosen RGs => RG Index
-> multiple experimental conditions can be
tested: one reference condition and up
to 6 different treatments
-> efficiency
calculation
via dilution row
-> manual efficiency input
-> data output in a graph with error bars
-> error estimation of
the calculated ratio using a Taylor's series
-> bugs removed in randomisation test
Short description of
REST-MCS
A survey of tools for
the analysis of quantitative PCR (qPCR) data
Stephan Pabinger, Stefan Rödiger,
Albert Kriegner, Klemens Vierlinger, Andreas
Weinhäusel
Biomolecular Detection and
Quantification 1 (2014) 23–33
Real-time
quantitative
polymerase-chain-reaction
(qPCR) is a standard technique in most
laboratories used for various applications in
basic research. Analysis of qPCR data is a crucial
part of the entire experiment, which has led to
the development of a plethora of methods. The
released tools either cover specific parts of the
workflow or provide complete analysis solutions.
Here, we surveyed 27 open-access software packages
and tools for the analysis of qPCR data. The
survey includes 8 Microsoft Windows, 5 web-based,
9 R-based and 5 tools from other platforms.
Reviewed packages and tools support the analysis
of different qPCR applications, such as RNA
quantification, DNA methylation, genotyping,
identification of copy number variations, and
digital PCR. We report an overview of the
functionality, features and specific requirements
of the individual software tools, such as data
exchange formats, availability of a graphical user
interface, included procedures for graphical data
presentation, and offered statistical methods. In
addition, we provide an overview about
quantification strategies, and report various
applications of qPCR. Our comprehensive survey
showed that most tools use their own file format
and only a fraction of the currently existing
tools support the standardized data exchange
format RDML. To allow a more streamlined and
comparable analysis of qPCR data, more vendors and
tools need to adapt the standardized format to
encourage the exchange of data between instrument
software, analysis tools, and researchers.
http://camper.cebitec.uni-bielefeld.de/
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CAmpER -
Real-time PCR analysis software
CAmpER - Calculation of Amplification
Efficiencies for RT-PCR
experiments is a tool for the automatic analysis
of real time PCR experiments.
Automatic analysis, annotation and storage
of real-time PCR experiments performed
with different real-time PCR systems, currently
the LightCycler
2, LC480, Rotor-Gene and Opticon.
If you want to
test CAmpER please email to jblom@cebitec.uni-bielefeld.de
System requirements for CAmpER 1.2:
- A HTML 4.x compatible web browser.
- A screen resolution of at least
1280x1024.
- Please enable Javascript.
- Please enable Cookies.
- The system has been tested with
Mozilla 1.1, Firefox 1.0, and Opera 7.3
- We recommend using the latest version
of Firefox.
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Management
and
automated
analysis of real-time quantitative PCR data
Introduction
Gene expression analysis is becoming increasingly
important in biological research and clinical
decision making, with real-time quantitative PCR
becoming the method of choice for expression
profiling of selected genes. Maturation of
chemistry and hardware has made the practical
performance of real-time quantitative PCR
measurements feasible for most laboratories.
However, accurate and straightforward mathematical
and statistical analysis of the raw data (cycle
threshold values) as well as the management of
growing data sets have become the major hurdles in
gene expression analyses. Since the software
provided along with the different detection
systems does not provide an adequate solution for
these issues, we developed qBase, a free software
program for the management and automated analysis
of real-time quantitative PCR data.
What is
qBase ? qBase
is a collection of macros for Microsoft Excel
(currently only Windows version) for the
management and automated analysis of real-time
quantitative PCR data. The program employs a
delta-Ct relative quantification model with PCR
efficiency correction and multiple reference gene
normalization. The qBase Browser allows data
storage and annotation by hierarchically
organizing real-time PCR runs into projects >
experiments > runs. It is compatible with the
export files from many currently available PCR
instrument softwares and provides easy access to
all your data, both raw and processed. The qBase
Analyzer contains an easy run (plate) editor,
performs quality control and inter-plate
calibration, converts Ct values into normalized
and rescaled quantities with proper error
propagation, and displays results both tabulated
and in graphs. The program can handle an unlimited
number of samples, genes and replicates, and
allows data from multiple runs to be processed
together (preceded by an inter-run calibration if
required). The possibility to use up to 5
reference genes allows reliable and robust
normalization of gene expression levels. qBase
allows easy exchange of data between users, and
exports tabulated data for further statistical
analyses using other dedicated software.
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qBASE+
Biogazelle is the
real-time PCR data-analysis company,
founded in 2007 as a Ghent University
spin-off company. Its founders have more
than 10 years of experience in real-time
PCR experiment design, assay development
and data-analysis. They wrote one of the
most influential papers on normalization
of gene expression and on data-analysis
(together cited more than one thousand
times in internal peer-reviewed articles).
Biogazelle's flagship
product qBase+ is
the most powerful, flexible, and
user-friendly real-time PCR data-analysis
software based on the proven geNorm and
qBase technology, enhanced with
proprietary algorithms and innovative
features. qBase+ is truly
accelerating your research.
Based
on years of experience, Biogazelle is also
offering hands-on courses on experiment
design and data-analysis, starting June
2008.
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qBase has now
been phased out and the professional
successor qBase+ is now
available from the real-time PCR
data-analysis company Biogazelle.
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Other qPCR related tools form
our group
geNorm
expression stability analysis of candidate reference
genes for accurate normalization
[Vandesompele et al., Genome Biology, 2002]
RTPrimerDB real-time
PCR primer and probe database with currently 3439
real-time PCR assays
[Pattyn et al., Nucleic Acids Research, 2003]
DART-PCR
Experimental validation of novel and
conventional approaches to quantitative
real-time PCR data analysis
Stuart N. Peirson, Jason N.
Butler and Russell G. Foster (2003)
Real-time PCR is being
used increasingly as the method of choice for mRNA
quantification, allowing rapid analysis of gene
expression from low quantities of starting
template. Despite a wide range of approaches, the
same principles underlie all data analysis, with
standard approaches broadly classiffed as either
absolute or relative. In this study we use a
variety of absolute and relative approaches of
data analysis to investigate nocturnal c-fos
expression in wild-type and retinally degenerate
mice. In addition, we apply a simple algorithm to
calculate the amplifcation effciency of every
sample from its amplifcation profle. We confrm
that nocturnal c-fos expression in the rodent eye
originates from the photoreceptor layer, with
around a 5-fold reduction in nocturnal c-fos
expression in mice lacking rods
and cones. Furthermore, we illustrate that
differences in the results obtained from absolute
and relative approaches are underpinned by
differences in the calculated PCR effciency. By
calculating the amplifcation effciency from the
samples under analysis, comparable results may be
obtained without the need for standard curves. We
have automated this method to provide a means of
streamlining the real-time PCR process, enabling
analysis of experimental samples based upon their
own reaction kinetics rather than those of
artificial standards.
Download
DART PCR version 1.0.xls
(Excel version)
Example_exp_data.xls
(Excel
version)
Peirson
DART
version 1 (PDF)
DART-PCR provides a
simple means of analysing real-time PCR data from
raw flurescence data. This allows an automatic
calculation of amplification kinetics, as well as
performing the subsequent calculations for
relative quantification and calculation of assay
variability. Amplification efficiencies are also
tested to dtect anomalus samples within groups
(outlayers) and differences between experimatal
groups (amplification equivalence).
GENEX - Gene Expression
Macro
The Gene Expression Macro
is a simple tool for calculating relative
expression values from real-time PCR data
generated by the iCycler iQ or MyiQ systems.
Bio-Rad developed the Gene Expression Macro
as a Microsoft Excel workbook containing
specialized data analysis functions. Use
this macro to save valuable time by
employing standard methods of relative gene
expression analysis in pre-designed,
easy-to-use Excel spreadsheets.
The macro workbooks provided here have
been tested with Excel 2000 and Excel
2003, running on a Windows 2000 or XP
platform. These files have not
been tested using any of the following
computing platforms:
- Windows 98
or Windows ME
- Excel on
the Macintosh
- Any other
workbook or spreadsheet programs
To download the
Gene Expression Macro, sample data, and
user's guide, select the appropriate
link(s) below:
Download Q-Gene
software
QGENE.ZIP Size:
300 kb
Quantitative
real-time
PCR represents a highly sensitive and powerful
technique for the quantitation of nucleic acids.
It has a tremendous potential for the
high-throughput analysis of gene expression in
research and routine diagnostics. However, the
major hurdle is not the practical
performance of the experiments themselves but
rather the efficient evaluation and the
mathematical and statistical analysis of the
enormous amount of data gained by this technology,
as these functions are not included in the
software provided by the manufacturers of thedetection systems.
In this work, we focus on the mathematical
evaluation and analysis of the data generated by
quantitative real-time PCR, the calculation
of the final results, the propagation of
experimental variation of the measured values to
the final results, and the statistical
analysis. We developed a Microsoft®
Excel®-based software application coded in Visual
Basic for Applications, called Q-Gene, which
addresses these points. Q-Gene manages and
expedites the planning, performance, and
evaluation of quantitative real-time PCR experiments, as well
as the mathematical and statistical analysis,
storage, and graphical presentation of the data.
The Q-Gene software application is a tool to cope
with complex quantitative real-time PCR
experiments at a high-throughput scale and
considerably expedites and rationalizes the
experimental setup, data analysis, and data
management while ensuring highest reproducibility.
Processing of
gene expression data generated by
quantitative
real-time RT-PCR.
Muller PY,
Janovjak H, Miserez AR, Dobbie Z.
Biotechniques
2002
Jun;32(6):1372-1378
Research Group
Cardiovascular Genetics, Institute of Biochemistry
and Genetics, University of Basel, Switzerland.
Quantitative real-time PCR
represents a highly sensitive and powerful
technique for the
quantitation of nucleic acids. It has a
tremendous potentialfor the high-throughput
analysis of gene expression in research and
routine diagnostics. However, the
major hurdle is not the practical
performance of the experiments
themselves
but rather the efficient evaluation and the
mathematical and statistical
analysis of the enormous amount of data
gained by this technology, as these
functions are not included in the software
provided by themanufacturers
of the detection systems. In this work, we
focus on the mathematical
evaluation and analysis of the data
generated by quantitative real-time PCR,
the calculation of the final results, the
propagation of experimental
variation of the measured values to the
final results, and the statistical
analysis. We developed a Microsoft
Excel-based software application
coded in
Visual Basic for Applications, called
Q-Gene, which addresses these
points.
Q-Gene manages and expedites the planning,
performance, and evaluation and quantitative
real-time PCR experiments, as well as the
mathematical and statistical
analysis, storage, and graphical
presentation of the data. The
Q-Gene
software application is a tool to cope with
complex quantitative real-time PCR
experiments at a high-throughput scale and
considerably expedites and
rationalizes the experimental setup, data
analysis, and data management
while
ensuring highest reproducibility.
Erratum for: Muller
PY,
Janovjak H, Miserez AR, Dobbie Z.
Processing of
gene expression data generated by quantitative
real-time RT-PCR.
Biotechniques. 2002 32(6): 1372-1378
In Table
1, the values in the column "Normalized
Expression" need to be replaced by the following
ones (top to bottom): 2.30E-03, 2.63E-03,
3.92E-03, 2.95E-03, 4.95E-04, 16.79.
Additionally, the values in the column "Mean
Normalized Expression" need to be replaced by
2.87E-03, 3.26E-04, 11.35. The difference
between the two calculation procedures according
to Table 2, Equation 2 and 3, respectively,
amounts to 2.8%. Furthermore, the corresponding
values in the discussion section need to be
replaced.
In all Equations of Table 2, the
indices "target" and "ref" of all variables need
to be swapped. In Equation 6, a plus sign needs
to be added between the two brackets under the
square-root. These Equations have also been
corrected in all Q-Gene software files.
It is important that you no longer use any
former versions of the Q-Gene software files
because these files yield wrong results!
It is intended to publish the erratum.
Q-Gene: processing
quantitative real-time RT–PCR data
Perikles Simon
Section for Neurobiology of the Eye, University
Eye Hospital Tuebingen, Calwerstr. 7/1, 72076
Tuebingen, Germany
Paper:
Online
Presentation.
Summary: Q-Gene
is
an application for the processing of quantitative
real-time RT–PCR data. It offers the user the
possibility to freely choose between two
principally different procedures to calculate
normalized gene expressions as either means of
Normalized Expressions or Mean Normalized
Expressions. In this contribution it will be shown
that the calculation of Mean Normalized
Expressions has to be used for processing simplex
PCR data, while multiplex PCR data should
preferably be processed by calculating Normalized
Expressions. The two procedures, which are
currently in widespread use and regarded as more
or less equivalent alternatives, should therefore
specifically be applied according to the
quantification procedure used.
qCalculator
version
1.0
Tool to calculate relative mRNA Gene Expression.
programmed by Ralf Gilsbach, version 1.0,
Institut of Pharmacology & Toxicology, University
of Bonn
Short
qCalculator description
Download software
qPCR-DAMS:
a Database Tool to Analyze, Manage, and
Store Both Relative and Absolute Quantitative
Real-Time PCR data.
Quantitative
real-time PCR is an important high throughput method
in biomedical sciences. However, existing software
has limitations in handling both relative and
absolute quantification. We designed qPCR-DAMS
(Quantitative PCR Data Analysis and Management
System), a database tool based on Access 2003, to
deal with such shortcomings by the addition of
integrated mathematical procedures. qPCR-DAMA allows
a user choose among four methods for data processing
within a single software package: (I) Ratio relative
quantification, (II) Absolute level, (III)
Normalized absolute expression, and (IV) Ratio
absolute quantification. qPCR-DAMS also provides a
tool for multiple reference gene normalization.
qPCR-DAMS has three quality control steps and a data
display system to monitor data variation. In
summary, qPCR-DAMS is a handy tool for real-time PCR
users.
LinRegPCR
LinRegPCR is
a program for the analysis of quantitative RT-PCR
(qPCR) data resulting from monitoring the PCR
reaction with SYBR green or similar fluorescent
dyes. The program determines a baseline
fluorescence and does a baseline subtraction. Then
a Window-of-Linearity is set and PCR efficiencies
per sample are calculated. With the mean PCR
efficiency per amplicon, the Ct value per sample
and the fluorescence threshold set to determnine
the Ct, the starting concentration per sample,
expressed in arbitrary fluorescence units, is
calculated => See below:
- Ramakers et al., NeuroSci Lett 2003;
- Ruijter et al., Nucleic Acids Research
2009.
Assumption-free analysis of quantitative
real-time PCR data
Ramakers
C, Ruijter JM, Deprez RH, Moorman AF. (2003)
Neurosci Lett 2003 Mar
13;339(1): 62-66
Department
of Anatomy and Embryology K2-283, Experimental and
Molecular
Cardiology Group, Academic Medical
Centre, University of Amsterdam, Meibergdreef
15, 1105 AZ, Amsterdam, The
Netherlands
Quantification of
mRNAs using real-time polymerase chain reaction
(PCR) by monitoring the
product formation with the fluorescent dye SYBR
Green I is being extensively
used in neurosciences, developmental biology, and
medical diagnostics. Most
PCR data analysis procedures assume that the PCR
efficiency for the
amplicon of interest is constant or even, in the
case of the comparative C(t)
method, equal to 2. The latter method already
leads to a 4-fold error when the PCR efficiencies vary over just a
0.04 range. PCR efficiencies of amplicons are usually calculated from standard
curves based on either known RNA inputs or
on dilution series of a reference
cDNA sample. In this paper we show that the
first approach can lead to PCR
efficiencies that vary over a 0.2 range, whereas
the second approach may be off by
0.26. Therefore, we propose linear regression
on the Log(fluorescence) per cycle
number data as an assumption-free method to
calculate starting concentrations of
mRNAs and PCR efficiencies for each sample.
The new
LinRegPCR version of the program (with an
updated manual) can be downloaded =>
http://LinRegPCR.nl
Amplification efficiency: linking baseline
and bias in the analysis of quantitative PCR
data
J. M. Ruijter1, C. Ramakers2, W. M. H.
Hoogaars1, Y. Karlen3, O. Bakker4, M. J. B. van
den Hoff1 and A. F. M. Moorman1
1Heart Failure Research Center, Academic
Medical Center, University of Amsterdam, The
Netherlands, 2Department of Neuroscience,
Faculty of Mental Health, University of
Maastricht, The Netherlands, 3Nestec Ltd, PTC
Orbe, Switzerland and 4Department of
Endocrinology and Metabolism, Academic Medical
Center, University of Amsterdam, The Netherlands
Nucleic Acids Research Advance Access
published online on February 22, 2009
Despite the central role of quantitative PCR
(qPCR) in the quantification of mRNA transcripts,
most analyses of qPCR data are still delegated to
the software that comes with the qPCR apparatus.
This is especially true for the handling of the
fluorescence baseline. This article shows that
baseline estimation errors are directly reflected
in the observed PCR efficiency values and are thus
propagated exponentially in the estimated starting
concentrations as well as ‘fold-difference’
results. Because of the unknown origin and
kinetics of the baseline fluorescence, the
fluorescence values monitored in the initial
cycles of the PCR reaction cannot be used to
estimate a useful baseline value. An algorithm
that estimates the baseline by reconstructing the
log-linear phase downward from the early plateau
phase of the PCR reaction was developed and shown
to lead to very reproducible PCR efficiency
values. PCR efficiency values were determined per
sample by fitting a regression line to a subset of
data points in the log-linear phase. The
variability, as well as the bias, in qPCR results
was significantly reduced when the mean of these
PCR efficiencies per amplicon was used in the
calculation of an estimate of the starting
concentration per sample.
The new
LinRegPCR version of the program (with an
updated manual) can be downloaded =>
http://LinRegPCR.nl
Dear LinRegPCR user,
We recently updated LinRegPCR to
implement the import and export of RDML
files
RDML was developed as a
standard for export, exchange, and storage of
quantitative PCR data and is supported by
several large qPCR system suppliers as well as
by data analysis software like qbase-plus.
LinRegPCR now forms a link between your qPCR
system and such statistical analysis software.
LinRegPCR can handle RDML versions 1.0 and 1.1,
as well as RDML files in which floating point
values are written with decimals points and
decimal commas. LinRegPCR will write the
analysis results to an RDML file, version 1.1,
with decimal points to maintain compatibilty
with the current RDML specification.
The RDML input option is
the main addition to LinRegPCR that was
implemented in 2012. There were also several
qPCR systems added to the list of input formats
from Excel files. For other minor changes in the
program, please have a look at the recent
updates listed on the LinRegPCR website (http://LinRegPCR.nl).
On our site you will
also find a link to a recent paper (Ruijter et
al., Methods 2012), in which LinRegPCR and other
publicly available PCR amplification curve
analysis programs were compared. This paper is
unique in the field of qPCR because all analysis
methods were applied by their original
developers, and thus in the currently
recommended way. The paper was co-authored by
the developers of these curve analysis programs
and members of the geNorm team, who performed
the statistical analysis. The datasets used for
this comparison, and the analysis results, can
be downloaded from http://qPCRDataMethods.hfrc.nl.
I hope you continue to
enjoy the use of LinRegPCR.
Best wishes for the
coming festive season and your future scientific
endeavours,
Jan M Ruijter
Addressing fluorogenic real-time qPCR
inhibition using the novel custom Excel file
system 'FocusField2-6GallupqPCRSet-upTool-001'
to attain consistently high fidelity qPCR
reactions.
Jack M. Gallup and Mark R. Ackermann
Department of Veterinary Pathology,
College of Veterinary Medicine, Iowa State
University. Ames, Iowa 50011-1250. USA.
Biol. Proced. Online 2006;8:87-152.
The
purpose of this manuscript is to discuss
fluorogenic real-time quantitative polymerase
chain reaction (qPCR) inhibition and to
introduce/define a novel Microsoft Excel-based
file system which provides a way to detect and
avoid inhibition, and enables investigators to
consistently design dynamically-sound, truly
LOG-linear qPCR reactions very quickly. The
qPCR problems this invention solves are
universal to all qPCR reactions, and it
performs all necessary qPCR set-up
calculations in about 52 seconds (using a
pentium 4 processor) for up to seven qPCR
targets and seventy-two samples at a time –
calculations that commonly take capable
investigators days to finish. We have named
this custom Excel-based file system
"FocusField2- 6GallupqPCRSet-upTool-001"
(FF2-6-001 qPCR set-up tool), and are in the
process of transforming it into professional
qPCR set-up software to be made available in
2007. The current prototype is already fully
functional.
PREXCEL-Q
is not a qPCR data analysis program - it is an
extensive qPCR validation, set-up and
receipe printout program for each step of
the qPCR process; for One-Step, Two-Step and LCM-one
or two-step qPCR Test Plate
set-ups, avoidance of inhibition by proper dynamic dilution
range identificaton and the subsequent final plate
set-ups.
The
‘PREXCEL-Q Method’ for qPCR
Jack M. Gallup, Mark R. Ackermann
Department of Veterinary Pathology, College
of Veterinary Medicine, Iowa State University,
Ames, Iowa, USA
International journal of Biomedical science
4(4) 2008
The
purpose
of this manuscript is to describe a reliable
approach to quantitative real-time polymerase
chain reaction (qPCR ) assay development and
project management, which is currently embodied in
the Excel 2003-based software program named
“PREXCEL-Q” (P-Q) (formerly known as
“FocusField2-6Gallup-qPCRS et-upTool-001,”
“FF2-6-001 qPCR set-up tool” or “Iowa State
University Research Foundation [ISURF] project
#03407”). Since its inception from 1997-2007, the
program has been well-received and requested
around the world and was recently unveiled by its
inventor at the 2008 Cambridge Healthtech
Institute’s Fourth Annual qPCR Conference in San
Diego, CA. P-Q was subsequently mentioned in a
review article by Stephen A. Bustin, an
acknowledged leader in the qPCR field. Due to its
success and growing popularity, and the fact that
P-Q introduces a unique/defined approach to qPCR,
a concise description of what the program is and
what it does has become important. Sample-related
inhibitory problems of the qPCR assay, sample
concentration limitations, nuclease-treatment,
reverse transcription (RT ) and master mix
formulations are all addressed by the program,
enabling investigators to quickly, consistently
and confidently design uninhibited,
dynamically-sound,
LOG-linear-amplification-capable,
high-efficiency-of-amplification reactions for any
type of qPCR. The current version of the program
can handle an infinite number of samples.
SoFAR: software
for fully automatic evaluation of real-time PCR
data.
Wilhelm J, Pingoud A, Hahn M.
Justus-Liebig-Universitat Giessen, Giessen, Germany.
Biotechniques. 2003 Feb;34(2):324-32
Quantitative
real-time
PCR has proven to be an extremely useful technique
in life sciences for many applications. Although a
lot of attention has been paid to the optimization
of the assay conditions, the analysis of the data
acquired is often done with software tools that do
not make optimum use of the information provided by
the data. Particularly, this is the case for
high-throughput analysis, which requires a careful
characterization and interpretation of the complete
data by suitable software. Here we present a
software solution for the robust, reliable,
accurate, and fast evaluation of real-time PCR data,
called SoFAR. The software automatically evaluates
the data acquired with the LightCycler system. It
applies new algorithms for an adaptive background
correction of signal trends, the calculation of the
effective signal noise, the automated identification
of the exponential phases, the adaptive smoothing of
the raw data, and the correction of melting curve
data. Finally, it provides information regarding the
validity of the results obtained. The SoFAR software
minimizes the time required for evaluation and
increases the accuracy and reliability of the
results. The software is available upon request.
Validation of an algorithm for
automatic quantification of nucleic acid
copy numbers by real-time polymerase chain
reaction
Wilhelm J, Pingoud A, Hahn M.
Anal Biochem. 2003 Jun 15;317(2):218-25.
Institut fur Biochemie, FB 08,
Justus-Liebig-Universitat Giessen,
Heinrich-Buff-Ring 58, D-35392 Giessen, Germany.
Real-time
quantitative polymerase chain reaction (PCR)
with on-line fluorescence
detection has become an important technique not
only for determination of the absolute or relative
copy number of nucleic acids but also for mutation
detection, which is usually done by measuring
melting curves. Optimum assay conditions have been
established for a variety of targets and
experimental setups, but only limited attention
has been directed to data evaluation and
validation of the results. In this work,
algorithms for the processing of real-time PCR
data are evaluated for several target sequences
(p53, IGF-1, PAI-1, Factor VIIc) and compared to
the results obtained by standard procedures. The
algorithms are implemented in software called
SoFAR, which allows fully automatic analysis of
real-time PCR data obtained with a Roche
LightCycler instrument. The software yields
results with considerably increased precision and
accuracy of quantifications. This is achieved
mainly by the correction of phase of the signal
curves. The melting curve data are corrected for
signal changes not due to the melting process and
are smoothed by fitting cubic splines. Therefore,
sensitivity, resolution, and accuracy of melting
curve analyses are improved.
http://www.metralabs.com/en/dindex.html
| SoFAR®is
a
software of biologists and medics for a
quantitative analysis and interpretation
of real time PCR measurements. Originally
it was developed by Dr. Jochen Wilhelm for
research on a precise quantifying of
tumour suppressor genes and is now
distributed and up-dated by MetraLabs®
GmbH exclusively. This software makes a
fully automatic analysis and
interpretation of measurement data
possible, which are written down by
LightCycler® (Roche Diagnostics®)
or RapidCycler® (Idaho
Technology). To meet the highest demands
of precision and safety in the analysis,
robust algorithms were developed that
guarantee reliable results even with
suboptimal data. In combination with a
thought through user friendly surface,
real time PCR measureings are easy, fast
and precise to analyse. |
Complete analysis
with just one mouse click
Simply open the file which is to analyse -
no other steps are needed. Therefore one
file is completely analysed with just one
mouse click. |
 |
Accurate
results
SoFAR controls automatically whether the
criteria for a correct quantitative
analysis are obliged. Included are
automatic recognition and evaluation of
the exponential phase of amplification
curves as well as the calculated CT
values. Curves which cannot be analysed
correctly are marked. |
 |
Always
best
possible results
An efficient noise-filtering of the raw
data of amplification and melting curves,
makes more precise results possible.
Independent signal changes from the
amplification are automatically recognised
and corrected. The automatic correction of
temperature dependent quenches at melting
curves also eliminates systematic errors
and increases the sensitivity of a melting
curve analysis. |
 |
Easy
data
export
All results can be printed, saved or
exported into other programmes as graphics
or in tables. Extensive report functions
make an exact documentation of all results
easy. Diagrams which can be exported or
copied in publishing quality can be
changed and transformed in the layout from
the user. |
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