4.7 Article

SCIGA: Software for large-scale, single-cell immunoglobulin repertoire analysis

Journal

GIGASCIENCE
Volume 10, Issue 9, Pages -

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/gigascience/giab050

Keywords

software; single-cell; immunoglobulin repertoires; COVID-19; antibody

Funding

  1. National Science Fund for Distinguished Young Scholars [82025022]
  2. Sanming Project for Medicine of Shenzhen [SZSM201612053]
  3. National Key Plan for Scientific Research and Development of China [2020YFC0848800, 2020YFC0844200]
  4. National Science and Technology Major Project of the Infectious Diseases [2018ZX10301404]
  5. Science and Technology Innovation Committee of Shenzhen Municipality [JSGG20200207155251653, 2020A1111350032, JCYJ20190809115617365, JSGG20200807171401008, JCYJ20200109 144201725, KQTD20200909113758004, JSGG20200225151410198]
  6. National Natural Science Foundation of China [82002140]
  7. Natural Science Foundation of Guangdong Province of China [2019A1515011197]

Ask authors/readers for more resources

A specialized software SCIGA was developed for precise and quick analysis of 10X single-cell immunoglobulin repertoires, which helps researchers to interpret B-cell immunoglobulin repertoires with paired heavy and light chain. SCIGA successfully identified four neutralizing antibodies against SARS-CoV-2 in samples from patients with COVID-19.
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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