sumrep: A Summary Statistic Framework for Immune Receptor Repertoire Comparison and Model Validation

Abstract

The adaptive immune system generates an incredible diversity of antigen receptors for B and T cells to keep dangerous pathogens at bay. The DNA sequences coding for these receptors arise by a complex recombination process followed by a series of productivity-based filters, as well as affinity maturation for B cells, giving considerable diversity to the circulating pool of receptor sequences. Although these datasets hold considerable promise for medical and public health applications, the complex structure of the resulting adaptive immune receptor repertoire sequencing (AIRR-seq) datasets makes analysis difficult. In this paper we introduce , an R package that efficiently performs a wide variety of repertoire summaries and comparisons, and show how can be used to perform model validation. We find that summaries vary in their ability to differentiate between datasets, although many are able to distinguish between covariates such as donor, timepoint, and cell type for BCR and TCR repertoires. We show that deletion and insertion lengths resulting from V(D)J recombination tend to be more discriminative characterizations of a repertoire than summaries that describe the amino acid composition of the CDR3 region. We also find that state-of-the-art generative models excel at recapitulating gene usage and recombination statistics in a given experimental repertoire, but struggle to capture many physiochemical properties of real repertoires.

AIRRscape: an interactive tool for exploring B-cell receptor repertoires and antibody responses

“…As AIRRscape is in active development, we note some limitations and also envision future enhancements. AIRRscape is primarily an exploratory tool focused on visualization but various metrics could be used to formally measure overlap between repertoires [RDI; 46,sumrep; 47]. AIRRscape does not visualize all of the sequences in the bulk BCR repertoire datasets; due to size and computing limitations in the Shiny application, large datasets are collapsed when V-gene + J-gene assignments as well as CDR3 amino acid motifs are identical.…”

B-cell receptor repertoire sequencing: Deeper digging into the mechanisms and clinical aspects of immune-mediated diseases

“… ( Fahnrich et al., 2017 ) ARGalaxy 2017 R a web-based tool for of BCR sequencing data analysis and visualization ( H et al., 2017 ) IGoR 2018 C++ a comprehensive tool that takes BCR or TCR sequencing data and quantifies and characterizes receptor generation from both cDNA and gDNA ( Marcou et al., 2018 ) sumrep 2019 R an R package that takes a wide variety of repertoire summaries and comparisons, and performs model validation. ( Olson et al., 2019 ) Platypus 2021 R an open-source platform providing a user-friendly interface for B cell receptor investigation from scRNA-seq experiments ( Yermanos et al., 2021 ) …”

Adaptive Immune Receptor Repertoire (AIRR) Community Guide to Repertoire Analysis

“…This is driven especially by variation in the first and second complementarity-determining regions (CDR1 and CDR2) of the genes, which contribute to the specificity and affinity of the immune receptor. Differences in the distribution of V genes used in the rearranged repertoire can indicate an antigen-specific response or unusual clonal expansions and can be evaluated with the function compareVGeneDistributions of the sumrep R package [20] (https://github.com/matsengrp/sumrep). The D and J gene strongly contributes to the CDR3 and can be compared using compareDGeneDistributions and compareJGeneDistributions.…”

“…The R package sumrep [20] provides functions to compare the CDR3 properties of two repertoires, such as the CDR3 length and a number of amino acid physicochemical properties [31,32].…”