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Processing of gene expression data generated by quantitative real-time RT-PCR.
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2002
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Molecular BiologyTranscriptomics TechnologyReal-time Polymerase Chain ReactionGene Expression ProfilingPolymerase Chain ReactionQuantitative AnalysisBiostatisticsMicroarray Data AnalysisMolecular Biological MethodQuantitative Real-time PcrGene ExpressionFunctional GenomicsBioinformaticsQuantitative Real-time Rt-pcrNatural SciencesComputational BiologyNucleic Acid AmplificationSystems BiologyMedicineNucleic Acids
Quantitative real‑time PCR is a highly sensitive, high‑throughput technique, yet its data evaluation and statistical analysis are not supported by manufacturer software, posing a major hurdle. The study aims to develop tools for mathematical evaluation, result calculation, variation propagation, and statistical analysis of qRT‑PCR data. The authors created Q‑Gene, a Microsoft Excel VBA application that streamlines planning, execution, analysis, storage, and graphical presentation of qRT‑PCR experiments. Q‑Gene effectively handles complex, high‑throughput qRT‑PCR experiments, accelerating setup, analysis, and data management while ensuring reproducibility.
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 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 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.