TY - JOUR T1 - Scirpy: A Scanpy extension for analyzing single-cell T-cell receptor sequencing data JF - bioRxiv DO - 10.1101/2020.04.10.035865 SP - 2020.04.10.035865 AU - Gregor Sturm AU - Tamas Szabo AU - Georgios Fotakis AU - Marlene Haider AU - Dietmar Rieder AU - Zlatko Trajanoski AU - Francesca Finotello Y1 - 2020/01/01 UR - http://biorxiv.org/content/early/2020/04/13/2020.04.10.035865.abstract N2 - 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.Competing Interest StatementThe authors have declared no competing interest. ER -