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 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.

中文翻译：

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Scirpy：用于分析单细胞 T 细胞受体测序数据的 Scanpy 扩展。

单细胞技术的进步使得以前所未有的分辨率和规模研究 T 细胞表型和库成为可能。用于有效分析这些大规模数据集的生物信息学方法有助于增进我们对适应性免疫反应的理解。然而，虽然可以使用成熟的解决方案来处理单细胞转录组，但没有简化的流程可用于 T 细胞受体的全面表征。在这里，我们提出了Scirpy，这是一个可扩展的 Python 工具包，它提供了对单细胞免疫库的分析和可视化的简化访问，以及与转录组数据的无缝集成。