<h1 align="center">
<img src="https://raw.githubusercontent.com/yutanagano/tidytcells/main/tidytcells.png" width=700>
</h1>
[](https://tidytcells.readthedocs.io)
[](https://github.com/yutanagano/tidytcells?tab=MIT-1-ov-file#readme)
[](https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2023.1276106)
`tidytcells` is a lightweight python package that cleans and standardizes T cell receptor (TR) and Major Histocompatibility (MH) data to be [IMGT](https://www.imgt.org/)-compliant.
The main purpose of the package is to solve the problem of parsing and collating together non-standardized TR datasets.
It is often difficult to compile TR data from multiple sources because the formats/nomenclature of how each dataset encodes TR and MH gene names are slightly different, or even inconsistent within themselves.
`tidytcells` can ameliorate this issue by auto-correcting and auto-standardizing your data.
Check out the [documentation page](https://tidytcells.readthedocs.io).
## Installation
### Via [PyPI](https://pypi.org/project/tidytcells/) (recommended)
`tidytcells` can be installed using `pip`:
```bash
$ pip install tidytcells
```
### From [source](https://github.com/yutanagano/tidytcells)
The source code for the package is available [on Github](https://github.com/yutanagano/tidytcells).
To install from source, clone the git repository, and run:
```bash
$ pip install .
```
from inside the project root directory.
## Citing tidytcells
To cite `tidytcells`, please refer to [this manuscript](https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2023.1276106).
## Useful links
- [Documentation](https://tidytcells.readthedocs.io)
- [PyPI page](https://pypi.org/project/tidytcells)
- [Publication page](https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2023.1276106)
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