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https://github.com/bobeobibo/phigaro

Phigaro is a scalable command-line tool for predicting phages and prophages
https://github.com/bobeobibo/phigaro

bioinformatics bioinformatics-analysis bioinformatics-pipeline bioinformatics-tool biological-data-analysis genomic-data-analysis genomic-regions genomics phage phages prophage

Last synced: 3 months ago
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Phigaro is a scalable command-line tool for predicting phages and prophages

Host: GitHub
URL: https://github.com/bobeobibo/phigaro
Owner: bobeobibo
License: mit
Created: 2017-08-21T10:33:28.000Z (about 7 years ago)
Default Branch: master
Last Pushed: 2024-01-08T18:29:37.000Z (10 months ago)
Last Synced: 2024-07-16T10:54:22.518Z (4 months ago)
Topics: bioinformatics, bioinformatics-analysis, bioinformatics-pipeline, bioinformatics-tool, biological-data-analysis, genomic-data-analysis, genomic-regions, genomics, phage, phages, prophage
Language: HTML
Homepage:
Size: 6.8 MB
Stars: 46
Watchers: 4
Forks: 15
Open Issues: 3
Metadata Files:
- Readme: README.md
- License: LICENSE.md

Awesome Lists containing this project

awesome-phages - Phigaro - Phigaro is a standalone command-line application that is able (Annotation / Prophage prediction)

README

# Phigaro v2.4.0
[![PyPI version](https://badge.fury.io/py/phigaro.svg)](https://badge.fury.io/py/phigaro)
![Conda installation](https://anaconda.org/bioconda/phigaro/badges/version.svg)
![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

Phigaro is a standalone command-line application that is able to detect prophage regions taking raw genome and metagenome assemblies as an input. It also produces dynamic annotated “prophage genome maps” and marks possible transposon insertion spots inside prophages. It is applicable for mining prophage regions from large metagenomic datasets.

## Updates tracker
You can find the information about updates and releases by [link.](https://github.com/bobeobibo/phigaro/blob/master/version_tracker.md)

## Documentation: Installation & Usage
Please, follow [the documentation link](https://phigaro.readthedocs.io/) to find installation and usage information.

## Methods overview
Open-reading frames (i.e. proteins) are predicted from the input FASTA file using Prodigal. Phage genes are annotated with prokaryotic viral orthologous groups (pVOGs) profile Hidden Markov Models (HMMs), which can be downloaded stand-alone from http://dmk-brain.ecn.uiowa.edu/pVOGs/. Each contig is represented as a sequence of phage and non-phage genes. A smoothing window algorithm (a triangular window function) determines regions with a high density of phage genes and therefore the prophage regions and boundaries, considering the pVOG annotations and the GC content.

## Known issues
Phigaro is tested on Linux systems. For MacOS, you may need to add the following softlink `ln -s /usr/libexec/locate.updatedb /usr/local/bin/updated` and run `brew install wget`. If you encounter any issues while running Phigaro on test data, please report them to us at [email protected].

## Publication
Elizaveta V. Starikova, Polina O. Tikhonova, Nikita A. Prianichnikov, Chris M. Rands, Evgeny M. Zdobnov, Vadim M. Govorun
Phigaro: high throughput prophage sequence annotation

- Bioinformatics, 2020; doi: https://doi.org/10.1093/bioinformatics/btaa250
- bioRxiv, 2019; doi: https://doi.org/10.1101/598243