Analysis of single-cell TCR repertoires and gene expression from multi-modal scRNA-seq data

Single-cell RNA and T-cell receptor (TCR) sequencing are powerful tools for dissecting T-cell diversity and function with unprecedented resolution. Analyzing transcripts and TCR sequences expressed by individual T-cells, enables comprehensive characterization of T-cell repertoires, antigen specificity and clonal dynamics which is fundamental in understanding the adaptive immune responses in various physiological and pathological conditions, including cancer, autoimmune diseases, and infectious diseases. To perform integrative analyses of multi-modal data from single-cell RNA and TCR sequencing experiments specialized bioinformatic tools are required. Here we exemplify the application of Scirpy, a versatile Python package specifically designed for single-cell TCR sequencing analysis, which streamlines the processing and analysis of TCR sequencing data. Scirpy offers a user-friendly framework for tasks like repertoire characterization, visualization, and clonotype identification. Moreover, Scirpy integrates seamlessly with other single-cell analysis tools from the scverse ecosystem, enabling comprehensive multi-modal data integration and downstream analyses.