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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...

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Autores principales: Ye, Haocheng, Cheng, Lin, Ju, Bin, Xu, Gang, Liu, Yang, Zhang, Shuye, Wang, Lifei, Zhang, Zheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
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.
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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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