4.7 Article

GEnView: a gene-centric, phylogeny-based comparative genomics pipeline for bacterial genomes and plasmids

Journal

BIOINFORMATICS
Volume 38, Issue 6, Pages 1727-1728

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btab855

Keywords

-

Funding

  1. Swedish Research Council VR [2018-05771, 2018-02835, 2019-03482]
  2. Swedish Research Council for Environment, Agriculture and Spatial Planning (FORMAS) [2018-00787]
  3. Formas [2018-00787] Funding Source: Formas
  4. Swedish Research Council [2019-03482] Funding Source: Swedish Research Council

Ask authors/readers for more resources

GEnView is a Python-based pipeline for comparative analysis of gene loci in a large number of bacterial genomes, providing users with automated, taxon-selective access to over 800,000 genomes and plasmids available in the NCBI Assembly and RefSeq databases.
Comparing genomic loci of a given bacterial gene across strains and species can provide insights into their evolution, including information on e.g. acquired mobility, the degree of conservation between different taxa or indications of horizontal gene transfer events. While thousands of bacterial genomes are available to date, there is no software that facilitates comparisons of individual gene loci for a large number of genomes. GEnView (Genetic Environment View) is a Python-based pipeline for the comparative analysis of gene-loci in a large number of bacterial genomes, providing users with automated, taxon-selective access to the >800.000 genomes and plasmids currently available in the NCBI Assembly and RefSeq databases, and is able to process local genomes that are not deposited at NCBI, enabling searches for genomic sequences and to analyze their genetic environments through the interactive visualization and extensive metadata files created by GEnView.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available