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AIRRscape: An interactive tool for exploring B-cell receptor repertoires and antibody responses
The sequencing of antibody repertoires of B-cells at increasing coverage and depth has led to the identification of vast numbers of immunoglobulin heavy and light chains. However, the size and complexity of these Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) datasets makes it difficult t...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9524643/ https://www.ncbi.nlm.nih.gov/pubmed/36126074 http://dx.doi.org/10.1371/journal.pcbi.1010052 |
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author | Waltari, Eric Nafees, Saba McCutcheon, Krista M. Wong, Joan Pak, John E. |
author_facet | Waltari, Eric Nafees, Saba McCutcheon, Krista M. Wong, Joan Pak, John E. |
author_sort | Waltari, Eric |
collection | PubMed |
description | The sequencing of antibody repertoires of B-cells at increasing coverage and depth has led to the identification of vast numbers of immunoglobulin heavy and light chains. However, the size and complexity of these Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) datasets makes it difficult to perform exploratory analyses. To aid in data exploration, we have developed AIRRscape, an R Shiny-based interactive web browser application that enables B-cell receptor (BCR) and antibody feature discovery through comparisons among multiple repertoires. Using AIRR-seq data as input, AIRRscape starts by aggregating and sorting repertoires into interactive and explorable bins of germline V-gene, germline J-gene, and CDR3 length, providing a high-level view of the entire repertoire. Interesting subsets of repertoires can be quickly identified and selected, and then network topologies of CDR3 motifs can be generated for further exploration. Here we demonstrate AIRRscape using patient BCR repertoires and sequences of published monoclonal antibodies to investigate patterns of humoral immunity to three viral pathogens: SARS-CoV-2, HIV-1, and DENV (dengue virus). AIRRscape reveals convergent antibody sequences among datasets for all three pathogens, although HIV-1 antibody datasets display limited convergence and idiosyncratic responses. We have made AIRRscape available as a web-based Shiny application, along with code on GitHub to encourage its open development and use by immuno-informaticians, virologists, immunologists, vaccine developers, and other scientists that are interested in exploring and comparing multiple immune receptor repertoires. |
format | Online Article Text |
id | pubmed-9524643 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-95246432022-10-01 AIRRscape: An interactive tool for exploring B-cell receptor repertoires and antibody responses Waltari, Eric Nafees, Saba McCutcheon, Krista M. Wong, Joan Pak, John E. PLoS Comput Biol Research Article The sequencing of antibody repertoires of B-cells at increasing coverage and depth has led to the identification of vast numbers of immunoglobulin heavy and light chains. However, the size and complexity of these Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) datasets makes it difficult to perform exploratory analyses. To aid in data exploration, we have developed AIRRscape, an R Shiny-based interactive web browser application that enables B-cell receptor (BCR) and antibody feature discovery through comparisons among multiple repertoires. Using AIRR-seq data as input, AIRRscape starts by aggregating and sorting repertoires into interactive and explorable bins of germline V-gene, germline J-gene, and CDR3 length, providing a high-level view of the entire repertoire. Interesting subsets of repertoires can be quickly identified and selected, and then network topologies of CDR3 motifs can be generated for further exploration. Here we demonstrate AIRRscape using patient BCR repertoires and sequences of published monoclonal antibodies to investigate patterns of humoral immunity to three viral pathogens: SARS-CoV-2, HIV-1, and DENV (dengue virus). AIRRscape reveals convergent antibody sequences among datasets for all three pathogens, although HIV-1 antibody datasets display limited convergence and idiosyncratic responses. We have made AIRRscape available as a web-based Shiny application, along with code on GitHub to encourage its open development and use by immuno-informaticians, virologists, immunologists, vaccine developers, and other scientists that are interested in exploring and comparing multiple immune receptor repertoires. Public Library of Science 2022-09-20 /pmc/articles/PMC9524643/ /pubmed/36126074 http://dx.doi.org/10.1371/journal.pcbi.1010052 Text en © 2022 Waltari et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Waltari, Eric Nafees, Saba McCutcheon, Krista M. Wong, Joan Pak, John E. AIRRscape: An interactive tool for exploring B-cell receptor repertoires and antibody responses |
title | AIRRscape: An interactive tool for exploring B-cell receptor repertoires and antibody responses |
title_full | AIRRscape: An interactive tool for exploring B-cell receptor repertoires and antibody responses |
title_fullStr | AIRRscape: An interactive tool for exploring B-cell receptor repertoires and antibody responses |
title_full_unstemmed | AIRRscape: An interactive tool for exploring B-cell receptor repertoires and antibody responses |
title_short | AIRRscape: An interactive tool for exploring B-cell receptor repertoires and antibody responses |
title_sort | airrscape: an interactive tool for exploring b-cell receptor repertoires and antibody responses |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9524643/ https://www.ncbi.nlm.nih.gov/pubmed/36126074 http://dx.doi.org/10.1371/journal.pcbi.1010052 |
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