Journal article
Phigaro: high-throughput prophage sequence annotation.
- Starikova EV Department of Molecular Biology and Genetics, Federal Research and Clinical Centre of Physical-Chemical Medicine, Moscow 119435, Russia.
- Tikhonova PO Department of Molecular Biology and Genetics, Federal Research and Clinical Centre of Physical-Chemical Medicine, Moscow 119435, Russia.
- Prianichnikov NA Department of Molecular Biology and Genetics, Federal Research and Clinical Centre of Physical-Chemical Medicine, Moscow 119435, Russia.
- Rands CM Department of Genetic Medicine and Development, University of Geneva Medical School and Swiss Institute of Bioinformatics, Geneva 1206, Switzerland.
- Zdobnov EM Department of Genetic Medicine and Development, University of Geneva Medical School and Swiss Institute of Bioinformatics, Geneva 1206, Switzerland.
- Ilina EN Department of Molecular Biology and Genetics, Federal Research and Clinical Centre of Physical-Chemical Medicine, Moscow 119435, Russia.
- Govorun VM Department of Molecular Biology and Genetics, Federal Research and Clinical Centre of Physical-Chemical Medicine, Moscow 119435, Russia.
- 2020-04-21
Published in:
- Bioinformatics (Oxford, England). - 2020
Statistics and Probability
Computational Theory and Mathematics
Biochemistry
Molecular Biology
Computational Mathematics
Computer Science Applications
English
SUMMARY
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.
AVAILABILITY AND IMPLEMENTATION
Source code for Phigaro is freely available for download at https://github.com/bobeobibo/phigaro along with test data. The code is written in Python.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
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.
AVAILABILITY AND IMPLEMENTATION
Source code for Phigaro is freely available for download at https://github.com/bobeobibo/phigaro along with test data. The code is written in Python.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
- Language
-
- English
- Open access status
- green
- Identifiers
-
- DOI 10.1093/bioinformatics/btaa250
- PMID 32311023
- Persistent URL
- https://sonar.ch/global/documents/279743
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