Advanced qPCR Analysis Pipeline: A Reproducible R Framework for Automated Gene Expression Quantification and Visualization

Abstract This software repository enables the automated, high-throughput analysis of Quantitative Real-Time PCR (qPCR) data using the R programming language. Developed to enhance reproducibility in molecular oncology and genetics research, this pipeline streamlines the transition from raw Cycle Threshold (Ct) values to statistically validated publication-quality figures.

Methodology The pipeline implements the comparative Ct method (Livak method, 2−ΔΔCt) to calculate relative gene expression fold changes normalized to a reference gene (e.g., GAPDH). It incorporates rigorous statistical testing, utilizing Welch’s t-test (accounting for unequal variances) to determine significance (p-values) and calculating 95% Confidence Intervals (CI) for precision estimation.

Key Capabilities:

• Data Parsing: Flexible input handling for standard CSV formats.
• Statistical Analysis: Automated computation of Fold Change, log2 Fold Change, Standard Error (SE), and significance levels.
• Advanced Visualization: Generation of high-resolution plots including Global Expression Profiles (Bar Plots), Treatment-Specific Volcano Plots, and Heatmaps with significance indicators.
• Granular Reporting: Production of individual gene-level plots for detailed inspection.

Reproducibility The package includes a standardized demo dataset (simulating differential expression of 10 target genes under multiple treatment conditions) to facilitate immediate testing and verification of the workflow.