VDJsolver

VDJsolver analyzes human immunoglobulin VDJ recombination to assign V, D, and J gene segments and characterize junctional modifications amid imprecise joining and somatic hypermutation.

Key Features:

• Algorithmic approaches: JointHMM implements a profile hidden Markov model for heavy-chain joint analysis and JointML implements a maximum-likelihood method that incorporates joint length and VH mutational status for D-gene assignment.
• Dataset performance: Evaluated on 6,329 clonally unrelated rearrangements, with JointML showing superior predictive performance for D-gene assignment compared to four other publicly available programs in both mutated and unmutated sequences.
• Accuracy and reliability: A conventional D gene was identified in 80% of unmutated sequences and 64% of mutated sequences, with <5% stochastic assignments in artificially permuted rearrangements.
• Recombination insights: Analysis found no significant evidence for DIR, chromosome 15 ORFs (OR15), use of multiple D genes, or VH replacements, and inverted D genes were observed in <1 per 1,000 sequences.
• Handling of sequence complexity: Explicitly addresses imprecise V-D-J joining and somatic hypermutations when assigning gene segments.

Scientific Applications:

• Immunogenetics: Facilitates analysis of VDJ recombination to investigate genetic determinants of antibody repertoires.
• Antibody diversity studies: Enables characterization of mechanisms generating antibody diversity through precise junction and segment assignment.
• Immune response variability: Supports investigations into variability of immune responses by resolving segment usage and junctional modifications.
• Large-scale genomic studies: Applicable to large datasets where accurate V/D/J assignment and analysis of mutational status are required.

Methodology:

VDJsolver uses a profile hidden Markov model (JointHMM) and a maximum-likelihood method (JointML) that account for joint length and VH mutational status to assign D genes.