Metadata-Version: 2.1
Name: argNorm
Version: 0.0.1rc1
Summary: Fast ARG normalization by mapping to the ARO ontology.
Home-page: https://github.com/BigDataBiology/argNorm
Author: Hui Chong
Author-email: huichong.me@gmail.com
License: MIT
Platform: UNKNOWN
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Programming Language :: Python :: 3.8
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Natural Language :: English
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE

# argNorm

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Fast ARG normalization by mapping to the ARO ontology.

This is a very-first implementation (**not ready for production**), but you're welcomed to try it and provide feedback to make it better. 

We recieve feedback on [GitHub Issue](https://github.com/BigDataBiology/argNorm/issues). 

## Supported databases

- [x] deeparg
- [ ] sarg
- [x] ncbi
- [x] argannot
- [x] megares
- [x] resfinder


## Installation

```bash
pip install argnorm
```

## Basic usage

Use `argnorm -h` too see available options.

```bash
argnorm [database] -i [original_annotation.tsv] -o [annotation_result_with_aro.tsv]
```

## Examples

```bash
argnorm deeparg -i examples/deeparg.deeparg.tsv -o tmp
argnorm megares -i examples/abricate.megares.tsv -o tmp
argnorm argannot -i examples/abricate.argannot.tsv -o tmp
argnorm resfinder -i examples/abricate.resfinder.tsv -o tmp
argnorm ncbi -i examples/abricate.ncbi.tsv -o tmp
```

## Maintainer

|   Name    | Email                 | Organization                                                 |
| :-------: | --------------------- | ------------------------------------------------------------ |
| Hui Chong | huichong.me@gmail.com | Research Assistant, Big Data Biology Lab, Fudan University |
| Svetlana Ugarcina | svetlana.ugarcina@gmail.com | Postdoc Researcher, Big Data Biology Lab, Fudan University |
| Luis Pedro Coelho | luis@luispedro.org | Principle Investigator, Big Data Biology Lab, Fudan University |

