Bayesian Inference of Allelic Inclusion Rates in the Human T Cell Receptor Repertoire

Carter, J. A., Preall, J. B., Atwal, G. S. (October 2019) Bayesian Inference of Allelic Inclusion Rates in the Human T Cell Receptor Repertoire. Cell Syst, 9 (5). pp. 475-482. ISSN 2405-4712 (Public Dataset)

URL: https://www.ncbi.nlm.nih.gov/pubmed/31677971
DOI: 10.1016/j.cels.2019.09.006

Abstract

A small population of alphabeta T cells is characterized by the expression of more than one unique T cell receptor (TCR); this outcome is the result of "allelic inclusion," that is, inclusion of both alpha- or beta-chain alleles during V(D)J recombination. Limitations in single-cell sequencing technology, however, have precluded comprehensive enumeration of these dual receptor T cells. Here, we develop and experimentally validate a fully Bayesian inference model capable of reliably estimating the true rate of alpha and beta TCR allelic inclusion across two different emulsion-barcoding single-cell sequencing platforms. We provide a database composed of over 51,000 previously unpublished allelic inclusion TCR sequence sets drawn from eight healthy individuals and show that allelic inclusion contributes a distinct and functionally important set of sequences to the human TCR repertoire. This database and a Python implementation of our statistical inference model are freely available at our Github repository (https://github.com/JasonACarter/Allelic_inclusion).

Item Type: Paper
Subjects: organs, tissues, organelles, cell types and functions > cell types and functions > cell types > T cells
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > T cells
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > T cells
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function > alleles
bioinformatics > computational biology > algorithms > machine learning
Investigative techniques and equipment > assays > Single cell sequencing
CSHL Authors:
Communities: CSHL labs > Atwal lab
CSHL labs > Preall lab
Depositing User: Matthew Dunn
Date: 22 October 2019
Date Deposited: 08 Nov 2019 15:45
Last Modified: 19 Dec 2019 17:45
Related URLs:
Dataset ID:
  • Code: https://github.com/JasonACarter/Allelic_inclusion
URI: https://repository.cshl.edu/id/eprint/38700

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