SeqFeatR

SeqFeatR identifies associations between mutation patterns in biological sequences and specific selection pressures to analyze how selection influences genomic variation.

Key Features:

• Identification of Mutation Patterns: Detects associations between mutation patterns and specific selection pressures in biological sequences.
• Statistical Methods: Implements both frequentist and Bayesian statistical methods for association analyses.
• Visualization of Results: Produces visualizations that link statistical outcomes to additional biological properties.
• Immunological Epitope Discovery: Supports discovery of new T cell epitopes within viral protein sequences for hosts with specific HLA types.

Scientific Applications:

• Evolutionary Biology: Characterizes how selection pressures shape sequence variation across genomes.
• Virology: Identifies mutation–feature associations in viral protein sequences.
• Immunology: Links sequence variation to host HLA-specific immune features, including T cell epitope identification.
• Vaccine Research: Informs selection of candidate T cell epitopes for vaccine-related studies.

Methodology:

Implemented as an R package that performs statistical association testing between mutation patterns and selection pressures using frequentist and Bayesian approaches and generates visualizations linking statistical results to additional biological properties.