IgGeneUsage

IgGeneUsage detects aberrant immunoglobulin gene usage between biological conditions using a probabilistic model analyzed by Bayesian inference.

Key Features:

• Bayesian Hierarchical Modeling: Employs Bayesian inference with hierarchical models to analyze complex gene usage data from high-throughput sequencing experiments of immune repertoires.
• Probabilistic Quantification: Quantifies differential immunoglobulin gene usage probabilistically rather than through qualitative or inadequate statistical methods.
• Avoidance of NHST Problems: Avoids common problems related to the current practice of null-hypothesis significance testing.

Scientific Applications:

• Immune Repertoire Profiling: Detects biases in immunoglobulin gene usage as an important task in immune repertoire profiling.
• Differential Gene Usage Analysis: Analyzes differential immunoglobulin gene usage between biological conditions, such as in response to viral infection or other adaptive immune challenges.

Methodology:

IgGeneUsage uses a probabilistic model analyzed computationally by Bayesian inference with hierarchical models.