Abstract
BackgroundSince its introduction quantitative real-time polymerase chain reaction (qPCR) has become the standard method for quantification of gene expression. Its high sensitivity, large dynamic range, and accuracy led to the development of numerous applications with an increasing number of samples to be analyzed. Data analysis consists of a number of steps, which have to be carried out in several different applications. Currently, no single tool is available which incorporates storage, management, and multiple methods covering the complete analysis pipeline.ResultsQPCR is a versatile web-based Java application that allows to store, manage, and analyze data from relative quantification qPCR experiments. It comprises a parser to import generated data from qPCR instruments and includes a variety of analysis methods to calculate cycle-threshold and amplification efficiency values. The analysis pipeline includes technical and biological replicate handling, incorporation of sample or gene specific efficiency, normalization using single or multiple reference genes, inter-run calibration, and fold change calculation. Moreover, the application supports assessment of error propagation throughout all analysis steps and allows conducting statistical tests on biological replicates. Results can be visualized in customizable charts and exported for further investigation.ConclusionWe have developed a web-based system designed to enhance and facilitate the analysis of qPCR experiments. It covers the complete analysis workflow combining parsing, analysis, and generation of charts into one single application. The system is freely available at
Highlights
Since its introduction quantitative real-time polymerase chain reaction has become the standard method for quantification of gene expression
The system is freely available at http:// genome.tugraz.at/QPCR
Implemented as a web application it can be accessed by a web browser from every network connected computer and supports the often decentralized work of biologists. It parses files generated by quantitative real-time polymerase chain reaction (qPCR) instruments, stores data and results in a database, and performs analyses on the imported data
Summary
Since its introduction quantitative real-time polymerase chain reaction (qPCR) has become the standard method for quantification of gene expression. In order to get biological meaningful results these basic calculations need to undergo further analyses such as normalization, averaging, and statistical tests [1]. To this end, a variety of different methods have been published describing the normalization of Cq values. The model proposed by Pfaffl [3] considers PCR efficiency for both the gene of interest and a reference gene and is an improvement over the classic ΔΔCq method. Hellemans et al [5] proposed an advanced method which considers gene-specific amplification efficiencies and allows normalization of Cq values with multiple reference genes based on the method proposed by Vandesompele et al [4]. It should be noted that these methods could differ substantially in their performance, because of the different assumptions they are based on
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