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Quantitative reverse transcription real-time polymerase chain reaction (RT-qPCR) is widely used for quantification of relative gene expression. Even though software has been developed to evaluate reference genes; no efficient and flexible program is available that is suitable for unlimited iterative computation necessary for analytical optimization. It is important that a computational program has a dynamic interface for user-controllable customization based on data quality, experimental design and specific research aims. To achieve this goal, SASqPCR is developed following the standard algorithm. It incorporates all functions important for RT-qPCR data analysis including assessment of PCR efficiencies, validation of internal reference genes and normalizers, normalization of confounding variations across samples and statistical comparisons of target gene expression in parallel samples. The program is highly automatic in data analyses and result output. The input data have no limitat
