Peacock, T;
Heather, JM;
Ronel, T;
Chain, B;
(2020)
Decombinator V4 – an improved AIRR-compliant software package for T cell receptor sequence annotation.
Bioinformatics
10.1093/bioinformatics/btaa758.
(In press).
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Abstract
MOTIVATION: Analysis of the T cell receptor repertoire is rapidly entering the general toolbox used by researchers interested in cellular immunity. The annotation of T cell receptors (TCRs) from raw sequence data poses specific challenges, which arise from the fact that TCRs are not germline encoded, and because of the stochastic nature of the generating process. RESULTS: In this study, we report the release of Decombinator V4, a tool for the accurate and fast annotation of large sets of TCR sequences. Decombinator was one of the early Python software packages released to analyse the rapidly increasing flow of T cell receptor repertoire sequence data. The Decombinator package now provides Python 3 compatibility, incorporates improved sequencing error and PCR bias correction algorithms, and provides output which conforms to the international standards proposed by the Adaptive Immune Receptor Repertoire Community. AVAILABILITY AND IMPLEMENTATION: The entire Decombinator suite is freely available at: https://github.com/innate2adaptive/Decombinator. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
| Type: | Article |
|---|---|
| Title: | Decombinator V4 – an improved AIRR-compliant software package for T cell receptor sequence annotation |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1093/bioinformatics/btaa758 |
| Publisher version: | http://dx.doi.org/10.1093/bioinformatics/btaa758 |
| Language: | English |
| Additional information: | © The Author(s) 2020. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Infection and Immunity |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10109884 |
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