Enhanced annotation of CD45RA to distinguish T cell subsets in single-cell RNA-seq via machine learning.

ABSTRACT:

Motivation

T cell heterogeneity presents a challenge for accurate cell identification, understanding their inherent plasticity, and characterizing their critical role in adaptive immunity. Immunologists have traditionally employed techniques such as flow cytometry to identify T cell subtypes based on a well-established set of surface protein markers. With the advent of single-cell RNA sequencing (scRNA-seq), researchers can now investigate the gene expression profiles of these surface proteins at the single-cell level. The insights gleaned from these profiles offer valuable clues and a deeper understanding of cell identity. However, CD45RA, the isoform of CD45 which distinguishes between naive/central memory T cells and effector memory/effector memory cells re-expressing CD45RA T c

SUBMITTER: Ran R 

PROVIDER: S-EPMC10676521 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature