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SCIGA: Software for large-scale, single-cell immunoglobulin repertoire analysis
BACKGROUND: B-cell immunoglobulin repertoires with paired heavy and light chain can be determined by means of 10X single-cell V(D)J sequencing. Precise and quick analysis of 10X single-cell immunoglobulin repertoires remains a challenge owing to the high diversity of immunoglobulin repertoires and a...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8478610/ https://www.ncbi.nlm.nih.gov/pubmed/34585238 http://dx.doi.org/10.1093/gigascience/giab050 |
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author | Ye, Haocheng Cheng, Lin Ju, Bin Xu, Gang Liu, Yang Zhang, Shuye Wang, Lifei Zhang, Zheng |
author_facet | Ye, Haocheng Cheng, Lin Ju, Bin Xu, Gang Liu, Yang Zhang, Shuye Wang, Lifei Zhang, Zheng |
author_sort | Ye, Haocheng |
collection | PubMed |
description | BACKGROUND: B-cell immunoglobulin repertoires with paired heavy and light chain can be determined by means of 10X single-cell V(D)J sequencing. Precise and quick analysis of 10X single-cell immunoglobulin repertoires remains a challenge owing to the high diversity of immunoglobulin repertoires and a lack of specialized software that can analyze such diverse data. FINDINGS: In this study, specialized software for 10X single-cell immunoglobulin repertoire analysis was developed. SCIGA (Single-Cell Immunoglobulin Repertoire Analysis) is an easy-to-use pipeline that performs read trimming, immunoglobulin sequence assembly and annotation, heavy and light chain pairing, statistical analysis, visualization, and multiple sample integration analysis, which is all achieved by using a 1-line command. Then SCIGA was used to profile the single-cell immunoglobulin repertoires of 9 patients with coronavirus disease 2019 (COVID-19). Four neutralizing antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were identified from these repertoires. CONCLUSIONS: SCIGA provides a complete and quick analysis for 10X single-cell V(D)J sequencing datasets. It can help researchers to interpret B-cell immunoglobulin repertoires with paired heavy and light chain. |
format | Online Article Text |
id | pubmed-8478610 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-84786102021-09-29 SCIGA: Software for large-scale, single-cell immunoglobulin repertoire analysis Ye, Haocheng Cheng, Lin Ju, Bin Xu, Gang Liu, Yang Zhang, Shuye Wang, Lifei Zhang, Zheng Gigascience Technical Note BACKGROUND: B-cell immunoglobulin repertoires with paired heavy and light chain can be determined by means of 10X single-cell V(D)J sequencing. Precise and quick analysis of 10X single-cell immunoglobulin repertoires remains a challenge owing to the high diversity of immunoglobulin repertoires and a lack of specialized software that can analyze such diverse data. FINDINGS: In this study, specialized software for 10X single-cell immunoglobulin repertoire analysis was developed. SCIGA (Single-Cell Immunoglobulin Repertoire Analysis) is an easy-to-use pipeline that performs read trimming, immunoglobulin sequence assembly and annotation, heavy and light chain pairing, statistical analysis, visualization, and multiple sample integration analysis, which is all achieved by using a 1-line command. Then SCIGA was used to profile the single-cell immunoglobulin repertoires of 9 patients with coronavirus disease 2019 (COVID-19). Four neutralizing antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were identified from these repertoires. CONCLUSIONS: SCIGA provides a complete and quick analysis for 10X single-cell V(D)J sequencing datasets. It can help researchers to interpret B-cell immunoglobulin repertoires with paired heavy and light chain. Oxford University Press 2021-09-28 /pmc/articles/PMC8478610/ /pubmed/34585238 http://dx.doi.org/10.1093/gigascience/giab050 Text en © The Author(s) 2021. Published by Oxford University Press GigaScience. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Technical Note Ye, Haocheng Cheng, Lin Ju, Bin Xu, Gang Liu, Yang Zhang, Shuye Wang, Lifei Zhang, Zheng SCIGA: Software for large-scale, single-cell immunoglobulin repertoire analysis |
title | SCIGA: Software for large-scale, single-cell immunoglobulin repertoire analysis |
title_full | SCIGA: Software for large-scale, single-cell immunoglobulin repertoire analysis |
title_fullStr | SCIGA: Software for large-scale, single-cell immunoglobulin repertoire analysis |
title_full_unstemmed | SCIGA: Software for large-scale, single-cell immunoglobulin repertoire analysis |
title_short | SCIGA: Software for large-scale, single-cell immunoglobulin repertoire analysis |
title_sort | sciga: software for large-scale, single-cell immunoglobulin repertoire analysis |
topic | Technical Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8478610/ https://www.ncbi.nlm.nih.gov/pubmed/34585238 http://dx.doi.org/10.1093/gigascience/giab050 |
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