IgGeneUsage

IgGeneUsage analyzes differential immunoglobulin (Ig) gene usage in immune repertoires by applying Bayesian hierarchical models to quantify biases from high-throughput sequencing data.

Key Features:

• Bayesian Hierarchical Modeling: Implements Bayesian hierarchical models to represent complex Ig gene usage patterns across samples.
• Probabilistic Quantification: Quantifies differential Ig gene usage as probabilities rather than relying solely on null-hypothesis significance testing.
• High-Throughput Data Compatibility: Designed to analyze Ig gene usage derived from high-throughput sequencing immune-repertoire datasets.

Scientific Applications:

• Viral infection studies: Detects differential Ig gene usage associated with immune responses to viral infections.
• Autoimmune disease research: Identifies Ig gene usage biases relevant to repertoire changes in autoimmune diseases.
• Vaccine development and immune monitoring: Supports analysis of repertoire shifts relevant to vaccine responses and immune monitoring.

Methodology:

Applies Bayesian inference via hierarchical models to probabilistically quantify differential Ig gene usage from high-throughput sequencing-derived immune-repertoire data.