Briefings in BioinformaticsBioinformaticsPeer-reviewed journal article
Quantitative Annotations of T-Cell Repertoire Specificity
Jia‐Qi LuoiD, Xueying WangiD, Yiping ZouiD, Lingxi CheniD, Wei LiuiD, Wei ZhangiD, Shuai Cheng LiiD
Abstract
The specificity of a T-cell receptor (TCR) repertoire determines personalized immune capacity. Existing methods have modelled the qualitative aspects of TCR specificity, while the quantitative aspects remained unaddressed. We developed a package, TCRanno, to quantify the specificity of TCR repertoires. Applying TCRanno to 4,195 TCR repertoires revealed quantitative changes in repertoire specificity upon infections, autoimmunity and cancers. Specifically, TCRanno found cytomegalovirus-specific TCRs in seronegative healthy individuals, supporting the possibility of abortive infections. TCRanno discovered age-accumulated fraction of SARS-CoV2-specific TCRs in pre-pandemic samples, which may explain the aggressive symptoms and age-related severity of COVID-19. TCRanno also identified the encounter of Hepatitis B antigens as a potential trigger of systemic lupus erythematosus. TCRanno annotations showed capability in distinguishing TCR repertoires of healthy and cancers including melanoma, lung and breast cancers. TCRanno may also facilitate single-cell TCRseq+gene expression data analyses by isolating T-cells with the specificity of interest.
- organism: human
- assay: CITE-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: drug response / drug discovery
- approach: statistical model
- Citations
- 6
- FWCI
- 0.65
- Field percentile
- top 38%
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