| qPCR
Software
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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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note
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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. |
|
|
