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VDJdb in 2019: database extension, new analysis infrastructure and a T-cell receptor motif compendium
Here, we report an update of the VDJdb database with a substantial increase in the number of T-cell receptor (TCR) sequences and their cognate antigens. The update further provides a new database infrastructure featuring two additional analysis modes that facilitate database querying and real-world...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6943061/ https://www.ncbi.nlm.nih.gov/pubmed/31588507 http://dx.doi.org/10.1093/nar/gkz874 |
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author | Bagaev, Dmitry V Vroomans, Renske M A Samir, Jerome Stervbo, Ulrik Rius, Cristina Dolton, Garry Greenshields-Watson, Alexander Attaf, Meriem Egorov, Evgeny S Zvyagin, Ivan V Babel, Nina Cole, David K Godkin, Andrew J Sewell, Andrew K Kesmir, Can Chudakov, Dmitriy M Luciani, Fabio Shugay, Mikhail |
author_facet | Bagaev, Dmitry V Vroomans, Renske M A Samir, Jerome Stervbo, Ulrik Rius, Cristina Dolton, Garry Greenshields-Watson, Alexander Attaf, Meriem Egorov, Evgeny S Zvyagin, Ivan V Babel, Nina Cole, David K Godkin, Andrew J Sewell, Andrew K Kesmir, Can Chudakov, Dmitriy M Luciani, Fabio Shugay, Mikhail |
author_sort | Bagaev, Dmitry V |
collection | PubMed |
description | Here, we report an update of the VDJdb database with a substantial increase in the number of T-cell receptor (TCR) sequences and their cognate antigens. The update further provides a new database infrastructure featuring two additional analysis modes that facilitate database querying and real-world data analysis. The increased yield of TCR specificity identification methods and the overall increase in the number of studies in the field has allowed us to expand the database more than 5-fold. Furthermore, several new analysis methods are included. For example, batch annotation of TCR repertoire sequencing samples allows for annotating large datasets on-line. Using recently developed bioinformatic methods for TCR motif mining, we have built a reduced set of high-quality TCR motifs that can be used for both training TCR specificity predictors and matching against TCRs of interest. These additions enhance the versatility of the VDJdb in the task of exploring T-cell antigen specificities. The database is available at https://vdjdb.cdr3.net. |
format | Online Article Text |
id | pubmed-6943061 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-69430612020-01-08 VDJdb in 2019: database extension, new analysis infrastructure and a T-cell receptor motif compendium Bagaev, Dmitry V Vroomans, Renske M A Samir, Jerome Stervbo, Ulrik Rius, Cristina Dolton, Garry Greenshields-Watson, Alexander Attaf, Meriem Egorov, Evgeny S Zvyagin, Ivan V Babel, Nina Cole, David K Godkin, Andrew J Sewell, Andrew K Kesmir, Can Chudakov, Dmitriy M Luciani, Fabio Shugay, Mikhail Nucleic Acids Res Database Issue Here, we report an update of the VDJdb database with a substantial increase in the number of T-cell receptor (TCR) sequences and their cognate antigens. The update further provides a new database infrastructure featuring two additional analysis modes that facilitate database querying and real-world data analysis. The increased yield of TCR specificity identification methods and the overall increase in the number of studies in the field has allowed us to expand the database more than 5-fold. Furthermore, several new analysis methods are included. For example, batch annotation of TCR repertoire sequencing samples allows for annotating large datasets on-line. Using recently developed bioinformatic methods for TCR motif mining, we have built a reduced set of high-quality TCR motifs that can be used for both training TCR specificity predictors and matching against TCRs of interest. These additions enhance the versatility of the VDJdb in the task of exploring T-cell antigen specificities. The database is available at https://vdjdb.cdr3.net. Oxford University Press 2020-01-08 2019-10-07 /pmc/articles/PMC6943061/ /pubmed/31588507 http://dx.doi.org/10.1093/nar/gkz874 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research. http://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/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Database Issue Bagaev, Dmitry V Vroomans, Renske M A Samir, Jerome Stervbo, Ulrik Rius, Cristina Dolton, Garry Greenshields-Watson, Alexander Attaf, Meriem Egorov, Evgeny S Zvyagin, Ivan V Babel, Nina Cole, David K Godkin, Andrew J Sewell, Andrew K Kesmir, Can Chudakov, Dmitriy M Luciani, Fabio Shugay, Mikhail VDJdb in 2019: database extension, new analysis infrastructure and a T-cell receptor motif compendium |
title | VDJdb in 2019: database extension, new analysis infrastructure and a T-cell receptor motif compendium |
title_full | VDJdb in 2019: database extension, new analysis infrastructure and a T-cell receptor motif compendium |
title_fullStr | VDJdb in 2019: database extension, new analysis infrastructure and a T-cell receptor motif compendium |
title_full_unstemmed | VDJdb in 2019: database extension, new analysis infrastructure and a T-cell receptor motif compendium |
title_short | VDJdb in 2019: database extension, new analysis infrastructure and a T-cell receptor motif compendium |
title_sort | vdjdb in 2019: database extension, new analysis infrastructure and a t-cell receptor motif compendium |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6943061/ https://www.ncbi.nlm.nih.gov/pubmed/31588507 http://dx.doi.org/10.1093/nar/gkz874 |
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