Consistency of VDJ rearrangement and substitution parameters enables accurate B cell receptor sequence annotation

TL;DR

This paper introduces a new non-parametric, allele-specific HMM model for B cell receptor sequence annotation, significantly improving accuracy over previous parametric models, and provides an efficient software implementation called partis.

Contribution

It develops a novel non-parametric HMM approach with per-allele parameters for BCR annotation, enhancing inference accuracy and efficiency.

Findings

Model using allele-specific categorical distributions improves annotation accuracy.

The partis software enables efficient, high-accuracy BCR sequence analysis.

Non-parametric modeling captures complex mutation and recombination patterns.

Abstract

VDJ rearrangement and somatic hypermutation work together to produce antibody-coding B cell receptor (BCR) sequences for a remarkable diversity of antigens. It is now possible to sequence these BCRs in high throughput; analysis of these sequences is bringing new insight into how antibodies develop, in particular for broadly-neutralizing antibodies against HIV and influenza. A fundamental step in such sequence analysis is to annotate each base as coming from a specific one of the V, D, or J genes, or from an N-addition (a.k.a. non-templated insertion). Previous work has used simple parametric distributions to model transitions from state to state in a hidden Markov model (HMM) of VDJ recombination, and assumed that mutations occur via the same process across sites. However, codon frame and other effects have been observed to violate these parametric assumptions for such coding sequences, suggesting that a non-parametric approach to modeling the recombination process could be useful. In our paper, we find that indeed large modern data sets suggest a model using parameter-rich per-allele categorical distributions for HMM transition probabilities and per-allele-per-position mutation probabilities, and that using such a model for inference leads to significantly improved results. We present an accurate and efficient BCR sequence annotation software package using a novel HMM "factorization" strategy. This package, called partis (https://github.com/psathyrella/partis/), is built on a new general-purpose HMM compiler that can perform efficient inference given a simple text description of an HMM.