In:
Frontiers in Immunology, Frontiers Media SA, Vol. 13 ( 2022-10-27)
Abstract:
T cell receptor (TCR) studies have grown substantially with the advancement in the sequencing techniques of T cell receptor repertoire sequencing (TCR-Seq). The analysis of the TCR-Seq data requires computational skills to run the computational analysis of TCR repertoire tools. However biomedical researchers with limited computational backgrounds face numerous obstacles to properly and efficiently utilizing bioinformatics tools for analyzing TCR-Seq data. Here we report pyTCR, a computational notebook-based solution for comprehensive and scalable TCR-Seq data analysis. Computational notebooks, which combine code, calculations, and visualization, are able to provide users with a high level of flexibility and transparency for the analysis. Additionally, computational notebooks are demonstrated to be user-friendly and suitable for researchers with limited computational skills. Our tool has a rich set of functionalities including various TCR metrics, statistical analysis, and customizable visualizations. The application of pyTCR on large and diverse TCR-Seq datasets will enable the effective analysis of large-scale TCR-Seq data with flexibility, and eventually facilitate new discoveries.
Type of Medium:
Online Resource
ISSN:
1664-3224
DOI:
10.3389/fimmu.2022.954078
DOI:
10.3389/fimmu.2022.954078.s001
DOI:
10.3389/fimmu.2022.954078.s002
DOI:
10.3389/fimmu.2022.954078.s003
DOI:
10.3389/fimmu.2022.954078.s004
DOI:
10.3389/fimmu.2022.954078.s005
DOI:
10.3389/fimmu.2022.954078.s006
DOI:
10.3389/fimmu.2022.954078.s007
DOI:
10.3389/fimmu.2022.954078.s008
Language:
Unknown
Publisher:
Frontiers Media SA
Publication Date:
2022
detail.hit.zdb_id:
2606827-8
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