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

作者：Gregor Sturm, Tamás Szabó, Georgios Fotakis, Marlene Haider, Dietmar Rieder, Zlatko Trajanoski, Francesca Finotello · 发表于：bioRxiv (Cold Spring Harbor Laboratory) · 年份：2020 · DOI：10.1101/2020.04.10.035865 · 被引用次数：27 · 研究领域：Single-cell and spatial transcriptomics、T-cell and B-cell Immunology、Immune Cell Function and Interaction

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