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. v1.1.0 - Advanced qPCR Analysis Pipeline This release provides an updated and reproducible R-based pipeline for qPCR data analysis using the Livak method (2^-ΔΔCt). Key updates Added standardized dummy qPCR dataset for reproducibility. Improved automated statistical analysis using Welch's t-test. Added fold change, log2 fold change, p-values, and 95% confidence intervals. Generated publication-quality visualizations including: Global bar plots Treatment-specific volcano plots Expression heatmaps Individual gene-level plots Updated documentation and citation metadata. Licensed under the MIT License. Citation Please cite the Zenodo archived version: Noorollahi, H. (2026). Advanced qPCR Analysis Pipeline: A Reproducible R Framework for Automated Gene Expression Quantification and Visualization (v1.1.0). Zenodo. https://doi.org/10.5281/zenodo.20528637