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...
Autores principales: | , , , |
---|---|
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 |