B-Cell Aware Analysis of Single-Cell Transcriptomics Data

Single-cell RNA sequencing (scRNA-seq) has facilitated the studies of cellular heterogeneity in many different biological contexts, including how B cells function and mediate immune responses to infection, malignancies, and autoimmunity. scRNA-seq as applied to B cells requires specific bioinformatics strategies, which consider the distinct biology of B cells and biological processes unique to these cells, such as somatic hypermutation (SHM) and class switch recombination (CSR). We present here a protocol that analyses scRNA-seq alignments and count matrices, as well as B-cell receptor sequencing data obtained in parallel to scRNA-seq. We highlight computational strategies to ensure cell clusters align with biologically relevant B-cell subsets and cell states. We provide practical guidance on how CSR and SHM information can be extracted from the data and utilized to build robust computational models of B-cell maturation.