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BioinformaticsBioinformaticsPeer-reviewed journal article

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

Gregor SturmiD, Tamás Géza SzabóiD, Georgios FotakisiD, Marlene HaideriD, Dietmar RiederiD, Zlatko TrajanoskiiD, Francesca FinotelloiD

PDFDOIPreprintCode

Abstract

SummaryAdvances 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 in cancer, but also in infectious diseases like COVID-19. 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 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 implementationScirpy source code and documentation are available at https://github.com/icbi-lab/scirpy.

Citations
221
FWCI
6.24
Field percentile
top 2%

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