Fast ARG normalization by mapping to the ARO ontology.
Project description
argNorm
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.
Supported databases
- deeparg
- sarg
- ncbi
- argannot
- megares
- resfinder
Installation
pip install argnorm
Basic usage
Use argnorm -h too see available options.
argnorm [database] -i [original_annotation.tsv] -o [annotation_result_with_aro.tsv]
Examples
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 | 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 |
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