NormqPCR

NormqPCR performs reference gene selection and normalization of real-time quantitative PCR (RT-qPCR) data to enable accurate comparative gene expression analysis.

Key Features:

• Optimal Reference Gene Selection: Integrates algorithms to evaluate stability and select optimal reference genes for normalization.
• Data Normalization: Normalizes RT-qPCR expression data using selected reference genes to correct technical variation.
• Integration with R/Bioconductor: Operates within R and Bioconductor and supports storing RT-qPCR data in an ExpressionSet-compatible object for downstream analysis.
• Comprehensive Workflow Support: Provides end-to-end functions from reading raw RT-qPCR data to supporting identification of differentially expressed genes.
• Real-World Application: Has been applied to real datasets to demonstrate effectiveness in practical research scenarios.

Scientific Applications:

• Gene Expression Studies: Enables reliable comparison of gene expression levels across conditions by providing accurate normalization.
• Differential Expression Analysis: Facilitates identification of genes that are upregulated or downregulated across experimental conditions after normalization.
• High-Throughput Data Analysis: Supports analysis of large RT-qPCR datasets using reproducible computational methods.

Methodology:

Imports RT-qPCR data into R (ExpressionSet-compatible), applies algorithms to evaluate and select stable reference genes, performs normalization using the selected reference genes to correct technical variation, and enables downstream differential expression analysis.