Predicting recognition between T cell receptors and epitopes with TCRGP.
Journal
PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922
Informations de publication
Date de publication:
03 2021
03 2021
Historique:
received:
08
04
2020
accepted:
17
02
2021
revised:
06
04
2021
pubmed:
26
3
2021
medline:
3
8
2021
entrez:
25
3
2021
Statut:
epublish
Résumé
Adaptive immune system uses T cell receptors (TCRs) to recognize pathogens and to consequently initiate immune responses. TCRs can be sequenced from individuals and methods analyzing the specificity of the TCRs can help us better understand individuals' immune status in different disorders. For this task, we have developed TCRGP, a novel Gaussian process method that predicts if TCRs recognize specified epitopes. TCRGP can utilize the amino acid sequences of the complementarity determining regions (CDRs) from TCRα and TCRβ chains and learn which CDRs are important in recognizing different epitopes. Our comprehensive evaluation with epitope-specific TCR sequencing data shows that TCRGP achieves on average higher prediction accuracy in terms of AUROC score than existing state-of-the-art methods in epitope-specificity predictions. We also propose a novel analysis approach for combined single-cell RNA and TCRαβ (scRNA+TCRαβ) sequencing data by quantifying epitope-specific TCRs with TCRGP and identify HBV-epitope specific T cells and their transcriptomic states in hepatocellular carcinoma patients.
Identifiants
pubmed: 33764977
doi: 10.1371/journal.pcbi.1008814
pii: PCOMPBIOL-D-20-00576
pmc: PMC8023491
doi:
Substances chimiques
Complementarity Determining Regions
0
Epitopes, T-Lymphocyte
0
Receptors, Antigen, T-Cell
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e1008814Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
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