Inference of B cell clonal families using heavy/light chain pairing information

TL;DR

This paper introduces a new method for inferring B cell clonal families by leveraging heavy/light chain pairing information from high-throughput sequencing, improving accuracy especially for challenging light chain data.

Contribution

It presents a novel approach to incorporate pairing information into clonal family inference, along with methods to correct imperfect pairing data and enhancements to the partis software.

Findings

Improved clustering accuracy using pairing information.

Effective correction methods for imperfect pairing data.

Enhanced software with new features for BCR analysis.

Abstract

Next generation sequencing of B cell receptor (BCR) repertoires has become a ubiquitous tool for understanding the antibody-mediated immune response: it is now common to have large volumes of sequence data coding for both the heavy and light chain subunits of the BCR. However, until the recent development of high throughput methods of preserving heavy/light chain pairing information, these samples contained no explicit information on which heavy chain sequence pairs with which light chain sequence. One of the first steps in analyzing such BCR repertoire samples is grouping sequences into clonally related families, where each stems from a single rearrangement event. Many methods of accomplishing this have been developed, however, none so far has taken full advantage of the newly-available pairing information. This information can dramatically improve clustering performance, especially for the light chain. The light chain has traditionally been challenging for clonal family inference because of its low diversity and consequent abundance of non-clonal families with indistinguishable naive rearrangements. Here we present a method of incorporating this pairing information into the clustering process in order to arrive at a more accurate partition of the data into clonally related families. We also demonstrate two methods of fixing imperfect pairing information, which may allow for simplified sample preparation and increased sequencing depth. Finally, we describe several other improvements to the partis software package (https://github.com/psathyrella/partis).