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

Gregor Sturm, Tamás Szabó, Georgios Fotakis, Marlene Haider, Dietmar Rieder, Zlatko Trajanoski, Francesca Finotello

2020Bioinformatics227 citationsDOIOpen Access PDF

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.

Topics & Concepts

Python (programming language)Computer scienceVisualizationScalabilityDocumentationSource codeComputational biologyOpen sourceSoftwareData miningBiologyProgramming languageDatabaseSingle-cell and spatial transcriptomicsT-cell and B-cell Immunologyvaccines and immunoinformatics approaches
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