Method for identification of condition-associated public antigen receptor sequences

Diverse repertoires of hypervariable immunoglobulin receptors (TCR and BCR) recognize antigens in the adaptive immune system. The development of immunoglobulin receptor repertoire sequencing methods makes it possible to perform repertoire-wide disease association studies of antigen receptor sequence...

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Autores principales: Pogorelyy, Mikhail V, Minervina, Anastasia A, Chudakov, Dmitriy M, Mamedov, Ilgar Z, Lebedev, Yuri B, Mora, Thierry, Walczak, Aleksandra M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2018
Materias:
Computational and Systems Biology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5873893/
https://www.ncbi.nlm.nih.gov/pubmed/29533178
http://dx.doi.org/10.7554/eLife.33050
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author Pogorelyy, Mikhail V
Minervina, Anastasia A
Chudakov, Dmitriy M
Mamedov, Ilgar Z
Lebedev, Yuri B
Mora, Thierry
Walczak, Aleksandra M
author_facet Pogorelyy, Mikhail V
Minervina, Anastasia A
Chudakov, Dmitriy M
Mamedov, Ilgar Z
Lebedev, Yuri B
Mora, Thierry
Walczak, Aleksandra M
author_sort Pogorelyy, Mikhail V
collection PubMed
description Diverse repertoires of hypervariable immunoglobulin receptors (TCR and BCR) recognize antigens in the adaptive immune system. The development of immunoglobulin receptor repertoire sequencing methods makes it possible to perform repertoire-wide disease association studies of antigen receptor sequences. We developed a statistical framework for associating receptors to disease from only a small cohort of patients, with no need for a control cohort. Our method successfully identifies previously validated Cytomegalovirus and type one diabetes responsive TCR [Formula: see text] sequences .
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spelling pubmed-58738932018-03-29 Method for identification of condition-associated public antigen receptor sequences Pogorelyy, Mikhail V Minervina, Anastasia A Chudakov, Dmitriy M Mamedov, Ilgar Z Lebedev, Yuri B Mora, Thierry Walczak, Aleksandra M eLife Computational and Systems Biology Diverse repertoires of hypervariable immunoglobulin receptors (TCR and BCR) recognize antigens in the adaptive immune system. The development of immunoglobulin receptor repertoire sequencing methods makes it possible to perform repertoire-wide disease association studies of antigen receptor sequences. We developed a statistical framework for associating receptors to disease from only a small cohort of patients, with no need for a control cohort. Our method successfully identifies previously validated Cytomegalovirus and type one diabetes responsive TCR [Formula: see text] sequences . eLife Sciences Publications, Ltd 2018-03-13 /pmc/articles/PMC5873893/ /pubmed/29533178 http://dx.doi.org/10.7554/eLife.33050 Text en © 2018, Pogorelyy et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Computational and Systems Biology
Pogorelyy, Mikhail V
Minervina, Anastasia A
Chudakov, Dmitriy M
Mamedov, Ilgar Z
Lebedev, Yuri B
Mora, Thierry
Walczak, Aleksandra M
Method for identification of condition-associated public antigen receptor sequences
title Method for identification of condition-associated public antigen receptor sequences
title_full Method for identification of condition-associated public antigen receptor sequences
title_fullStr Method for identification of condition-associated public antigen receptor sequences
title_full_unstemmed Method for identification of condition-associated public antigen receptor sequences
title_short Method for identification of condition-associated public antigen receptor sequences
title_sort method for identification of condition-associated public antigen receptor sequences
topic Computational and Systems Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5873893/
https://www.ncbi.nlm.nih.gov/pubmed/29533178
http://dx.doi.org/10.7554/eLife.33050
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