Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Peacock, Thomas, Heather, James M, Ronel, Tahel, Chain, Benny
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8098023/
https://www.ncbi.nlm.nih.gov/pubmed/32853330
http://dx.doi.org/10.1093/bioinformatics/btaa758
_version_ 1783688427678466048
author Peacock, Thomas
Heather, James M
Ronel, Tahel
Chain, Benny
author_facet Peacock, Thomas
Heather, James M
Ronel, Tahel
Chain, Benny
author_sort Peacock, Thomas
collection PubMed
description 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.
format Online
Article
Text
id pubmed-8098023
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-80980232021-05-10 Decombinator V4: an improved AIRR-C compliant-software package for T-cell receptor sequence annotation? Peacock, Thomas Heather, James M Ronel, Tahel Chain, Benny Bioinformatics Applications Notes 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. Oxford University Press 2020-08-27 /pmc/articles/PMC8098023/ /pubmed/32853330 http://dx.doi.org/10.1093/bioinformatics/btaa758 Text en © The Author(s) 2020. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Peacock, Thomas
Heather, James M
Ronel, Tahel
Chain, Benny
Decombinator V4: an improved AIRR-C compliant-software package for T-cell receptor sequence annotation?
title Decombinator V4: an improved AIRR-C compliant-software package for T-cell receptor sequence annotation?
title_full Decombinator V4: an improved AIRR-C compliant-software package for T-cell receptor sequence annotation?
title_fullStr Decombinator V4: an improved AIRR-C compliant-software package for T-cell receptor sequence annotation?
title_full_unstemmed Decombinator V4: an improved AIRR-C compliant-software package for T-cell receptor sequence annotation?
title_short Decombinator V4: an improved AIRR-C compliant-software package for T-cell receptor sequence annotation?
title_sort decombinator v4: an improved airr-c compliant-software package for t-cell receptor sequence annotation?
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8098023/
https://www.ncbi.nlm.nih.gov/pubmed/32853330
http://dx.doi.org/10.1093/bioinformatics/btaa758
work_keys_str_mv AT peacockthomas decombinatorv4animprovedairrccompliantsoftwarepackagefortcellreceptorsequenceannotation
AT heatherjamesm decombinatorv4animprovedairrccompliantsoftwarepackagefortcellreceptorsequenceannotation
AT roneltahel decombinatorv4animprovedairrccompliantsoftwarepackagefortcellreceptorsequenceannotation
AT chainbenny decombinatorv4animprovedairrccompliantsoftwarepackagefortcellreceptorsequenceannotation