qDATA - an R application implementing a practical framework for analyzing quantitative Real-Time PCR data

Abstract

Gene expression assays that are based on quantitative real-time PCR (qRT-PCR) method are still very popular, therefore, we developed qDATA, a modern open-source R based bioinformatics application that offers a quick and intuitive analysis of raw cycle threshold (Ct) values. The application relies on a straightforward specific data input consisting in Ct values and a few other mandatory fields specifying the experimental and control groups, as well as the target and house-keeping genes. Afterwards, it automatically performs descriptive statistics, normality and statistical testing on 2-{Delta}Ct (or {Delta}Ct) and 2-{Delta}{Delta}Ct terms calculated with Livaks method. Each computation is indicated in dedicated tabs that display their output consisting in dynamic data tables and publishing quality graphs. We also detail a qRT-PCR data analysis framework that depends on performing exhaustive {Delta}Ct calculations within discrete biological replicates (BRs). The Livak formula is used for the complete sets of available data. These prerequisites arguably lead to an improved data analysis and statistical relevance. In order to maximize the relevance of the results we recommend using at least three BRs and three technical replicates. The efficiency of our computing approach was tested with qDATA using input Ct values corresponding to immune related gene expression evaluated in experimental infection of Drosophila melanogaster and summer versus winter Apis mellifera workers, respectively. Our results reveal that our working strategy is very reliable and highlight the efficacy and performance of qDATA application.