Skip to main content

A Pyrodigal extension to predict genes in giant viruses and viruses with alternative genetic code.

Project description

🔥🦠 Pyrodigal-gv Stars

A Pyrodigal extension to predict genes in giant viruses and viruses with alternative genetic code.

Actions Coverage License PyPI Bioconda AUR Wheel Python Versions Python Implementations Source GitHub issues Changelog Downloads

🗺️ Overview

Pyrodigal is a Python module that provides Cython bindings to Prodigal, an efficient gene finding method for genomes and metagenomes based on dynamic programming.

pyrodigal-gv is a small extension module for pyrodigal which distributes additional metagenomic models for giant viruses and viruses that use alternative genetic codes, first provided by Antônio Camargo in prodigal-gv. The new models are the following:

  • Acanthamoeba polyphaga mimivirus
  • Paramecium bursaria Chlorella virus
  • Acanthocystis turfacea Chlorella virus
  • VirSorter2's NCLDV gene model
  • Topaz (genetic code 15)
  • Agate (genetic code 15)
  • Gut phages (genetic code 15)
  • Gut phages (genetic code 11) × 5

🔧 Installing

pyrodigal-gv can be installed directly from PyPI as a universal wheel that contains all required data files:

$ pip install pyrodigal-gv

💡 Example

Just use the provided ViralGeneFinder class instead of the usual GeneFinder from pyrodigal, and the new viral models will be used automatically in meta mode:

import Bio.SeqIO
import pyrodigal_gv

record = Bio.SeqIO.read("sequence.gbk", "genbank")

orf_finder = pyrodigal_gv.ViralGeneFinder(meta=True)
for i, pred in enumerate(orf_finder.find_genes(bytes(record.seq))):
    print(f">{record.id}_{i+1}")
    print(pred.translate())

ViralGeneFinder has an additional keyword argument, viral_only, which can be set to True to run gene calling using only viral models.

🔨 Command line

pyrodigal-gv comes with a very simple command line similar to Prodigal and pyrodigal:

$ pyrodigal-gv -i <input_file.fasta> -a <gene_translations.fasta> -d <gene_sequences.fasta>

Contrary to prodigal and pyrodigal, the pyrodigal-gv script runs in meta mode by default! Running in single mode can be done with pyrodigal-gv -p single but the results will be exactly the same as pyrodigal, so why would you ever do this ⁉️

🔖 Citation

If you use the features provided by pyrodigal-gv beyond the base Pyrodigal functionality, please cite the original manuscript detailing these extensions:

Camargo, A. P., Roux, S., Schulz, F., Babinski, M., Xu, Y., Hu, B., ... and Kyrpides, N. C. (2023). Identification of mobile genetic elements with geNomad. Nature Biotechnology, 1-10.

Pyrodigal is scientific software, with a published paper in the Journal of Open-Source Software. Please cite both Pyrodigal and Prodigal if you are using it in an academic work, for instance as:

Pyrodigal (Larralde, 2022), a Python library binding to Prodigal (Hyatt et al., 2010).

Detailed references are available on the Publications page of the online documentation.

💭 Feedback

⚠️ Issue Tracker

Found a bug ? Have an enhancement request ? Head over to the GitHub issue tracker if you need to report or ask something. If you are filing in on a bug, please include as much information as you can about the issue, and try to recreate the same bug in a simple, easily reproducible situation.

🏗️ Contributing

Contributions are more than welcome! See CONTRIBUTING.md for more details.

📋 Changelog

This project adheres to Semantic Versioning and provides a changelog in the Keep a Changelog format.

⚖️ License

This library is provided under the GNU General Public License v3.0. The Prodigal code was written by Doug Hyatt and is distributed under the terms of the GPLv3 as well. See vendor/Prodigal/LICENSE for more information. The giant virus and alternative genetic code virus parameters were created by Antônio Camargo.

This project is in no way not affiliated, sponsored, or otherwise endorsed by the original Prodigal authors. It was developed by Martin Larralde during his PhD project at the European Molecular Biology Laboratory in the Zeller team.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyrodigal_gv-0.3.2.tar.gz (851.5 kB view details)

Uploaded Source

Built Distribution

pyrodigal_gv-0.3.2-py2.py3-none-any.whl (849.9 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file pyrodigal_gv-0.3.2.tar.gz.

File metadata

  • Download URL: pyrodigal_gv-0.3.2.tar.gz
  • Upload date:
  • Size: 851.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.5

File hashes

Hashes for pyrodigal_gv-0.3.2.tar.gz
Algorithm Hash digest
SHA256 aeeff43daec2c4aec7830ae2400799aa90bf273bcca86656ef239bee8d7e5ea5
MD5 383df36967a594f8ccffc97c520ee784
BLAKE2b-256 397a07567d680f418f8fc42ff7ce38752f312fd622744755afc11fa21555d265

See more details on using hashes here.

File details

Details for the file pyrodigal_gv-0.3.2-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for pyrodigal_gv-0.3.2-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 cd6d922d7495ff853a7385ef8abe68498113c177a5ded3d07f93c28b8c990120
MD5 6e9b72261c867eb07c186293551492a3
BLAKE2b-256 d68fe78b92bc836a7b50a3497ee655983561dec4ac2df06136f0c55e59a00144

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page