Scirpy: a Scanpy extension for analyzing single-cell T-cell receptor-sequencing data.


Journal

Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944

Informations de publication

Date de publication:
15 09 2020
Historique:
received: 11 04 2020
revised: 08 06 2020
accepted: 24 06 2020
pubmed: 3 7 2020
medline: 4 3 2021
entrez: 3 7 2020
Statut: ppublish

Résumé

Advances in single-cell technologies have enabled the investigation of T-cell phenotypes and repertoires at unprecedented resolution and scale. Bioinformatic methods for the efficient analysis of these large-scale datasets are instrumental for advancing our understanding of adaptive immune responses. However, while well-established solutions are accessible for the processing of single-cell transcriptomes, no streamlined pipelines are available for the comprehensive characterization of T-cell receptors. Here, we propose single-cell immune repertoires in Python (Scirpy), a scalable Python toolkit that provides simplified access to the analysis and visualization of immune repertoires from single cells and seamless integration with transcriptomic data. Scirpy source code and documentation are available at https://github.com/icbi-lab/scirpy. Supplementary data are available at Bioinformatics online.

Identifiants

pubmed: 32614448
pii: 5866543
doi: 10.1093/bioinformatics/btaa611
pmc: PMC7751015
doi:

Substances chimiques

Receptors, Antigen, T-Cell 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

4817-4818

Subventions

Organisme : European Research Council
ID : 786295
Pays : International
Organisme : Austrian Science Fund FWF
ID : T 974
Pays : Austria

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press.

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Auteurs

Gregor Sturm (G)

Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, Innsbruck 6020, Austria.

Tamas Szabo (T)

Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, Innsbruck 6020, Austria.
Biocenter, Institute of Developmental Immunology, Medical University of Innsbruck, Innsbruck 6020, Austria.

Georgios Fotakis (G)

Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, Innsbruck 6020, Austria.

Marlene Haider (M)

Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, Innsbruck 6020, Austria.

Dietmar Rieder (D)

Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, Innsbruck 6020, Austria.

Zlatko Trajanoski (Z)

Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, Innsbruck 6020, Austria.

Francesca Finotello (F)

Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, Innsbruck 6020, Austria.

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Classifications MeSH