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qPCR
Software
Download page
REST
- Relative Expression Software Tool:
Important
Notes !
REST
description:
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Further
qPCR software applications:
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Important
note !
All downloaded zipped REST files are password
protected !
The
Excel spreadsheet ZIP files of all REST software
versions are password protected. To get the password by automatic
response please
contact genequan@wzw.tum.de
or contact password@gene-quantification.info
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sent by e-mail to you.
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Quantification
Newsletter called qPCR NEWS and
new information about real-time PCR hardware, software and chemistries.
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
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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qBASEPlus
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 qBasePlus 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. qBasePlus
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 qBasePlus
is now available from the
real-time PCR data-analysis company Biogazelle.
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qBase
relative quantification framework and software for management and
automated analysis of real-time quantitative PCR data. Hellemans J,
Mortier G, De Paepe A, Speleman F, Vandesompele J. Genome Biol.
2007;8(2): R19.
qBASE
Talk at the qPCR 2007 symposium
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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.
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 from
Frequently
asked questions and an update history of the program can be found
at http://LinRegPCR.nl
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. |
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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. |
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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. |
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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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