Scirpy: a Scanpy Extension for Analyzing Single-cell T-cell Receptor-sequencing Data

Overview

Journal Bioinformatics

Publisher Oxford University Press

Specialty Biology

Date 2020 Jul 3

PMID 32614448

Citations 88

Authors

Gregor Sturm

Tamas Szabo

Georgios Fotakis

Marlene Haider

Dietmar Rieder

Zlatko Trajanoski

Francesca Finotello

Affiliations

Soon will be listed here.

Abstract

Summary: 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.

Availability And Implementation: Scirpy source code and documentation are available at https://github.com/icbi-lab/scirpy.

Supplementary Information: Supplementary data are available at Bioinformatics online.

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