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Phigaro: high-throughput prophage sequence annotation.
Starikova, Elizaveta V; Tikhonova, Polina O; Prianichnikov, Nikita A; Rands, Chris M; Zdobnov, Evgeny M; Ilina, Elena N; Govorun, Vadim M.
Afiliación
  • 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.
Bioinformatics ; 36(12): 3882-3884, 2020 06 01.
Article en En | MEDLINE | ID: mdl-32311023
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Profagos / Secuenciación de Nucleótidos de Alto Rendimiento Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2020 Tipo del documento: Article País de afiliación: Rusia Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Profagos / Secuenciación de Nucleótidos de Alto Rendimiento Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2020 Tipo del documento: Article País de afiliación: Rusia Pais de publicación: Reino Unido