Citing tidytcells

To cite this software, please refer to the manuscript below:

Details

AUTHOR	Nagano Yuta , Chain Benjamin
TITLE	tidytcells: standardizer for TR/MH nomenclature
JOURNAL	Frontiers in Immunology
VOLUME	14
YEAR	2023
URL	https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2023.1276106
DOI	10.3389/fimmu.2023.1276106
ISSN	1664-3224

Abstract

T cell receptors (TR) underpin the diversity and specificity of T cell activity. As such, TR repertoire data is valuable both as an adaptive immune biomarker, and as a way to identify candidate therapeutic TR. Analysis of TR repertoires relies heavily on computational analysis, and therefore it is of vital importance that the data is standardized and computer-readable. However in practice, the usage of different abbreviations and non-standard nomenclature in different datasets makes this data pre-processing non-trivial. tidytcells is a lightweight, platform-independent Python package that provides easy-to-use standardization tools specifically designed for TR nomenclature. The software is open-sourced under the MIT license and is available to install from the Python Package Index (PyPI). At the time of publishing, tidytcells is on version 2.0.0.

BibTex

@ARTICLE{10.3389/fimmu.2023.1276106,

AUTHOR={Nagano, Yuta  and Chain, Benjamin },

TITLE={tidytcells: standardizer for TR/MH nomenclature},

JOURNAL={Frontiers in Immunology},

VOLUME={14},

YEAR={2023},

URL={https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2023.1276106},

DOI={10.3389/fimmu.2023.1276106},

ISSN={1664-3224},

ABSTRACT={<p>T cell receptors (TR) underpin the diversity and specificity of T cell activity. As such, TR repertoire data is valuable both as an adaptive immune biomarker, and as a way to identify candidate therapeutic TR. Analysis of TR repertoires relies heavily on computational analysis, and therefore it is of vital importance that the data is standardized and computer-readable. However in practice, the usage of different abbreviations and non-standard nomenclature in different datasets makes this data pre-processing non-trivial. tidytcells is a lightweight, platform-independent Python package that provides easy-to-use standardization tools specifically designed for TR nomenclature. The software is open-sourced under the MIT license and is available to install from the Python Package Index (PyPI). At the time of publishing, tidytcells is on version 2.0.0.</p>}}