DOI: 10.1101/490102Dec 7, 2018Paper

Clustering based approach for population level identification of condition-associated T-cell receptor β-chain CDR3 sequences

BioRxiv : the Preprint Server for Biology
Dawit A YohannesDario Greco


Motivation: Deep immune receptor sequencing, Repseq, provides unprecedented opportunities to identify condition-associated T-cell clones, represented by T-cell receptor (TCR) CDR3 sequences. TCR profiling has potential value for increasing immunopathological understanding of various diseases, and holds considerable clinical relevance. However, due to the immense diversity of the immune repertoire, identification of condition relevant TCR CDR3s from total repertoires has so far been limited either to mostly "public" CDR3 sequences, which are shared across unrelated individuals, or to comparisons of CDR3 frequencies from multiple samples from the same individual. A methodology for the identification of condition-associated TCR CDR3s by population level comparison of groups of Repseq samples is currently lacking. Results: We implemented a computational pipeline that allows population level comparison of Repseq sample groups at the level of the immune repertoire sub-units that are shared across individuals. These sub-units (or sub-repertoires) represent shared immuno-genomic features across individuals that potentially encode common signatures in the immune response to antigens. The method first performs unsupervised clustering of ...Continue Reading

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