A viral identification tool using machine learning with nucleotide and protein features
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Table of Contents

1. About VirBrant
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
4. Roadmap
5. Contributing
6. License
7. Contact
8. Acknowledgements

About VirBrant

This project was created to identify viral contigs in metagenomics. Add details about project and images

Getting Started

To get a local copy up and running follow these simple example steps.

Prerequisites

VirBrant requires Python 3 and the following libraries (if installling through pip, libraries are automatically install)

• pandas
• scikit-learn
• biopython

Installation

VirBrant can only be forked from this repository. Once forked, enter into the files and compile the kmer counting program.

## git download here

cd VirBrant/scripts
tar xvf kmer-counter-master.zip
cd kmer-counter-master
make

Usage

VirBrant works as a python script. Once install via pip, VirBrant the command can be accessed. To get the help screen type:

VirBrant -h

The paramters of VirBrant are:

• -i: Input Fasta [required]
• -o: Output Directory [optional]

Running VirBrant

VirBrant without a sequencing file and renaming the output

cd VirBrant
scripts/VirBrant.py -i data/Test/Viral_contigs.fasta -o data/Test/Output

Roadmap

Current Version: 0.0.1

Improvements to be made:

• Reduce feature space to allow for smaller file processing
• Grid search hyper parameters for models
• Build into python package

See the open issues for a list of proposed features (and known issues).

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Cody Glickman - @glickman_Cody - [email protected]

Project Link: https://github.com/Strong-Lab/VirBrant

Acknowledgements

• James Costello
• Michael Strong
• Jo Hendrix