Metadata-Version: 2.1
Name: gcgc
Version: 0.12.2.dev1
Summary: GCGC is a preprocessing library for biological sequence model development.
Home-page: http://gcgc.trenthauck.com/
License: MIT
Author: Trent Hauck
Author-email: trent@trenthauck.com
Requires-Python: >=3.6,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Dist: biopython (>=1.76,<2.0)
Requires-Dist: click (>=7.0,<8.0)
Requires-Dist: pydantic (>=1.1,<2.0)
Requires-Dist: sentencepiece (>=0.1,<0.2)
Requires-Dist: typing-extensions (>=3.7,<4.0)
Project-URL: Repository, https://github.com/tshauck/gcgc
Description-Content-Type: text/markdown

# GCGC

> GCGC is a tool for feature processing on Biological Sequences.

[![](https://github.com/tshauck/gcgc/workflows/Run%20Tests%20and%20Lint/badge.svg)](https://github.com/tshauck/gcgc/actions?query=workflow%3A%22Run+Tests+and+Lint%22)
[![](https://img.shields.io/pypi/v/gcgc.svg)](https://pypi.python.org/pypi/gcgc)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.2329966.svg)](https://doi.org/10.5281/zenodo.2329966)
[![code style black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

## Installation

GCGC is primarily intended to be used as part of a larger workflow inside
Python, but it can also be used as a docker container.

To install via pip:

```sh
$ pip install gcgc
```

And to pull the docker image:

```sh
$ docker pull docker.io/thauck/gcgc
```

## Documentation

The GCGC documentation is at [gcgc.trenthauck.com](http://gcgc.trenthauck.com),
please see it for an example.

## Citing GCGC

If you use GCGC in your research, cite it with the following:

```
@misc{trent_hauck_2018_2329966,
  author       = {Trent Hauck},
  title        = {GCGC},
  month        = dec,
  year         = 2018,
  doi          = {10.5281/zenodo.2329966},
  url          = {https://doi.org/10.5281/zenodo.2329966}
}
```

