Decombinator V4: an improved AIRR compliant-software package for T-cell receptor sequence annotation?


Journal

Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944

Informations de publication

Date de publication:
05 05 2021
Historique:
received: 21 05 2020
revised: 15 07 2020
accepted: 20 08 2020
pubmed: 28 8 2020
medline: 4 6 2021
entrez: 28 8 2020
Statut: ppublish

Résumé

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. 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. The entire Decombinator suite is freely available at: https://github.com/innate2adaptive/Decombinator. Supplementary data are available at Bioinformatics online.

Identifiants

pubmed: 32853330
pii: 5898187
doi: 10.1093/bioinformatics/btaa758
pmc: PMC8098023
doi:

Substances chimiques

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

876-878

Commentaires et corrections

Type : ErratumIn

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press.

Références

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Auteurs

Thomas Peacock (T)

Division of Infection and Immunity, UCL, WC1E 6BT, London, UK.
CoMPLEX, Department of Computer Science, UCL, WC1E 7JG, London, UK.

James M Heather (JM)

Massachusetts General Hospital Cancer Center and Harvard Medical School, Boston, MA 02115, USA.

Tahel Ronel (T)

Division of Infection and Immunity, UCL, WC1E 6BT, London, UK.
Cancer Institute, UCL, WC1E 6DD, London, UK.

Benny Chain (B)

Division of Infection and Immunity, UCL, WC1E 6BT, London, UK.
CoMPLEX, Department of Computer Science, UCL, WC1E 7JG, London, UK.

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Classifications MeSH