qDATA - an R application implementing a practical framework for analyzing quantitative real-time PCR data

Area of Science:

• Bioinformatics
• Molecular Biology
• Genomics

Background:

• Quantitative real-time PCR (qRT-PCR) is a widely used method for gene expression analysis.
• Existing analysis methods can be complex and time-consuming.
• There is a need for intuitive and efficient tools for qRT-PCR data interpretation.

Purpose of the Study:

• To develop qDATA, an open-source R-based application for streamlined qRT-PCR data analysis.
• To provide a user-friendly interface for analyzing raw cycle threshold (Ct) values.
• To enhance the statistical relevance and reliability of qRT-PCR data analysis.

Main Methods:

• Development of qDATA, an R-based bioinformatics application.
• Input of raw Ct values and experimental/control group information.
• Automatic calculation of descriptive statistics, normality tests, and statistical tests on 2^-ΔCt and 2^-ΔΔCt values using Livak's method.
• Implementation of a framework for exhaustive ΔCt calculations within biological replicates (BRs).

Main Results:

• qDATA offers a quick and intuitive analysis of raw Ct values.
• The application automatically performs statistical analyses, including normality and significance testing.
• Testing on gene expression data from *Drosophila melanogaster* and *Apis mellifera* confirmed the reliability and performance of qDATA.

Conclusions:

• qDATA provides an efficient and reliable method for qRT-PCR data analysis.
• The proposed framework enhances statistical relevance through comprehensive ΔCt calculations.
• qDATA is a valuable tool for researchers working with gene expression assays.