qPCR Software Download page


REST - Relative Expression Software Tool:
Important Notes !

REST description:
Further qPCR software applications:
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  The password will instantly sent by e-mail to you.

By receiving your requested passwords, we will include your e-mail address to our Gene-Qunatification.info and real-time-PCR.info  mailing list, and you will receive our monthly appearing Gene 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

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.


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 ]
=> download here:    rest-384-beta-9august2006.zip

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 ]

=> download here:    rest-mcs-beta-9august2006.zip

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/

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.



logo aBase   

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.




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.

qBase has now been phased out and the professional successor qBase+ is now available from the real-time PCR data-analysis company Biogazelle.




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


logo RDML

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.

Please see attached Dr. Bustin's letter of endorsement of the program to get a feel for what the program really is.

PREXCEL-Q (which is 35 inter-linked Excel files) can only be licensed from Iowa State University by contacting Dr. Dario Valenzuela first at Iowa State University Research Foundation (ISURF)  at:  dariov@iastate.edu - and then I personally send the 35 files and password to each new user.

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.


©  editor@gene-quantification.info