Abstract
T cell receptors (TCR) and gene expression provide two complementary and essential aspects in T cell understanding, yet their diversity presents challenges in integrative analysis. We introduce TCRclub, a novel method integrating single-cell RNA sequencing data and single-cell TCR sequencing data using local harmony to identify functionally similar T cell groups, termed ‘clubs’. We applied TCRclub to 298,106 T cells across seven datasets encompassing various diseases. First, TCRclub outperforms the state-of-the-art methods in clustering T cells on a dataset with over 400 verified peptide-major histocompatibility complex categories. Second, TCRclub reveals a transition from activated to exhausted T cells in cholangiocarcinoma patients. Third, TCRclub discovered the pathways that could intervene in response to anti-PD-1 therapy for patients with basal cell carcinoma by analyzing the pre-treatment and post-treatment samples. Furthermore, TCRclub unveiled different T-cell responses and gene patterns at different severity levels in patients with COVID-19. Hence, TCRclub aids in developing more effective immunotherapeutic strategies for cancer and infectious diseases. © The Author(s) 2024.
| Original language | English |
|---|---|
| Pages (from-to) | 1329-1345 |
| Journal | Molecular Systems Biology |
| Volume | 20 |
| Issue number | 12 |
| Online published | 4 Nov 2024 |
| DOIs | |
| Publication status | Published - Dec 2024 |
Research Keywords
- Integration
- Local Harmony
- Single-Cell Analysis
- T-Cell Clustering
Publisher's Copyright Statement
- This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/