Citing tidytcells
=================

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

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

.. code-block:: 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>}}