ReadqPCR

ReadqPCR imports and analyzes raw real-time reverse transcription quantitative PCR (RT-qPCR) data to support normalization and differential gene expression analysis within the R/Bioconductor environment.

Key Features:

• Data Importation: Functions to import raw RT-qPCR data from various platforms directly into R.
• ExpressionSet Compatibility: Stores imported data in Bioconductor ExpressionSet objects for integration with other R workflows.
• Reference Gene Selection: Provides reference gene selection algorithms to identify appropriate reference genes for normalization.
• Data Normalization: Includes functions to normalize RT-qPCR data using selected reference genes to correct technical variation.
• Differential Expression Analysis: Enables downstream identification of differential gene expression between samples after normalization.

Scientific Applications:

• Gene Expression Studies: Quantitative analysis of transcriptional activity using RT-qPCR across conditions or treatments.
• Validation of High-throughput Data: Use of RT-qPCR data to validate findings from high-throughput sequencing experiments.
• Comparative Genomics: Comparison of gene expression profiles across samples, species, or experimental groups.

Methodology:

Computational steps explicitly include importing raw RT-qPCR data into R, storing data in ExpressionSet objects, selecting reference genes via provided algorithms, performing normalization using the selected reference genes, and conducting differential expression analysis.