CorMut

CorMut detects and quantifies correlated mutations at codon and amino acid levels to identify evolutionary pressures and compare mutation correlation patterns between distinct evolutionary conditions.

Key Features:

• Computation of Correlated Mutations: Computes correlated mutations at both codon and amino acid levels.
• Multiple Analytical Methods: Implements three classical methods—conditional selection pressure, mutual information, and Jaccard index—for detecting correlated mutations.
• Network Representation: Represents results as correlation mutation networks to analyze relationships among correlated sites.
• Comparative Analysis: Compares correlated mutations between two distinct evolutionary conditions.
• Detection of Positive Selection Sites (optional): Identifies sites under positive selection prior to correlation analysis.

Scientific Applications:

• Understanding Genetic Mechanisms: Analyzes correlated mutations to infer genetic mechanisms underlying molecular evolution.
• Comparative Evolutionary Studies: Compares correlated mutation patterns to study evolutionary divergence and adaptation across conditions.
• Network Analysis in Genomics: Uses network representations of mutation correlations to investigate complex relationships within genomic data.

Methodology:

Optionally detect sites under positive selection, then compute correlations among sites to identify correlated mutations.