RAbHIT

RAbHIT infers V(D)J haplotypes and gene deletions from repertoires of rearranged antibody sequences using a Bayesian framework to resolve chromosomal phasing in highly repetitive immunoglobulin loci from short-read sequencing.

Key Features:

• Haplotype Inference (Chromosomal Phasing): Infers V(D)J haplotypes to determine chromosomal phasing of antibody variable-region loci.
• Bayesian Framework: Employs a Bayesian statistical framework to analyze repertoires of rearranged V(D)J sequences for probabilistic assignment of haplotypes.
• Gene Deletion Inference: Detects gene deletions within immunoglobulin loci from sequence repertoires.
• Applicability to B-cell Types and Library Protocols: Applies to sequences from both naïve and non-naïve B cells and accommodates different library preparation protocols.
• Short-read Alignment Handling: Addresses alignment ambiguity of short reads in highly repetitive antibody loci to improve inference robustness.

Scientific Applications:

• Clinical Genetics: Provides haplotype and deletion information to support investigation of genetic factors associated with disease susceptibility.
• Immunogenomics Research: Enables study of the genetic architecture of antibody diversity and its implications for immune response by resolving complex variation in immunoglobulin loci.

Methodology:

Uses a Bayesian framework to analyze repertoires of rearranged V(D)J sequences to infer chromosomal haplotypes and gene deletions while addressing short-read alignment challenges in highly repetitive immunoglobulin loci.