Current annotation strategies for T cell phenotyping of single-cell RNA-seq data - Mullan, Kerry A.; de Vrij, Nicky; Valkiers, Sebastiaan; Meysman, Pieter (Frontiers in Immunology, 2023)
Single-cell RNA sequencing (scRNA-seq) has become a popular technique for interrogating the diversity and dynamic nature of cellular gene expression and has numerous advantages in immunology. For example, scRNA-seq, in contrast to bulk RNA sequencing, can discern cellular subtypes within a population, which is important for heterogenous populations such as T cells. Moreover, recent advancements in the technology allow parallel capturing of the highly diverse T cell receptor (TCR) sequence with the gene expression. However, the field of single-cell RNA sequencing data analysis is still hampered by a lack of gold-standard cell phenotype annotation. This problem is particularly severe for T cells due to their heterogeneity in both their gene expression and their TCR. While current cell phenotype annotation tools can discern major cell populations from each other, labelling T cell subtypes remains problematic. In this review, we identify the common automated strategy for annotating T cells and their sub-populations, as well as describe what crucial information is still missing in these tools.