↓ Skip to main content

PLOS

Genomer — A Swiss Army Knife for Genome Scaffolding

Overview of attention for article published in PLOS ONE, June 2013
Altmetric Badge

Mentioned by

twitter
26 X users

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
34 Mendeley
citeulike
2 CiteULike
Title
Genomer — A Swiss Army Knife for Genome Scaffolding
Published in
PLOS ONE, June 2013
DOI 10.1371/journal.pone.0066922
Pubmed ID
Authors

Michael D. Barton, Hazel A. Barton

Abstract

The increasing accessibility and reduced costs of sequencing has made genome analysis accessible to more and more researchers. Yet there remains a steep learning curve in the subsequent computational steps required to process raw reads into a database-deposited genome sequence. Here we describe "Genomer," a tool to simplify the manual tasks of finishing and uploading a genome sequence to a database. Genomer can format a genome scaffold into the common files required for submission to GenBank. This software also simplifies updating a genome scaffold by allowing a human-readable YAML format file to be edited instead of large sequence files. Genomer is written as a command line tool and is an effort to make the manual process of genome scaffolding more robust and reproducible. Extensive documentation and video tutorials are available at http://next.gs.

X Demographics

X Demographics

The data shown below were collected from the profiles of 26 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 9%
Netherlands 1 3%
Brazil 1 3%
Canada 1 3%
Sweden 1 3%
Japan 1 3%
Spain 1 3%
Unknown 25 74%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 38%
Student > Bachelor 4 12%
Professor 4 12%
Student > Postgraduate 4 12%
Professor > Associate Professor 3 9%
Other 5 15%
Unknown 1 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 71%
Computer Science 3 9%
Biochemistry, Genetics and Molecular Biology 2 6%
Engineering 2 6%
Environmental Science 1 3%
Other 0 0%
Unknown 2 6%