rtpcr: a package for statistical analysis and graphical presentation of qPCR data in R

Background Quantitative real-time polymerase chain reaction (qRT-PCR or qPCR) is widely used in molecular biology research. Various analysis methods are employed to interpret qPCR data and measure mRNA levels of target genes under different experimental conditions. Results The rtpcr package was developed for amplification efficiency calculation, statistical analysis, and graphical presentation of qPCR data in R. It uses a general calculation methodology that accommodates up to two reference genes and amplification efficiency values, including the Pfaffl method. Depending on the experimental design, rtpcr functions apply a t -test (for experiments with a two-level factor), analysis of variance (ANOVA), or analysis of covariance (ANCOVA) (for experiments with more than two levels or factors) to calculate fold change (FC) or relative expression (RE) of a target gene. The functions also provide standard errors and confidence intervals for the means and support statistical mean comparisons. To facilitate usage, the package includes example datasets. It also offers ggplot-based visualizations with customizable arguments, allowing users to tailor the graphical output. Conclusions In summary, the rtpcr package is a useful and user-friendly tool for analyzing real-time PCR data from experiments involving up to three different factors. Built on a general methodology, it provides robust calculations and comprehensive graphical outputs, making it a valuable resource for researchers working with qPCR data.