Journal Article

Figmop: a profile HMM to identify genes and bypass troublesome gene models in draft genomes

David M. Curran, John S. Gilleard and James D. Wasmuth

in Bioinformatics

Volume 30, issue 22, pages 3266-3267
Published in print November 2014 | ISSN: 1367-4803
Published online August 2014 | e-ISSN: 1460-2059 | DOI: https://dx.doi.org/10.1093/bioinformatics/btu544
Figmop: a profile HMM to identify genes and bypass troublesome gene models in draft genomes

More Like This

Show all results sharing this subject:

  • Bioinformatics and Computational Biology

GO

Show Summary Details

Preview

Motivation: Gene models from draft genome assemblies of metazoan species are often incorrect, missing exons or entire genes, particularly for large gene families. Consequently, labour-intensive manual curation is often necessary. We present Figmop (Finding Genes using Motif Patterns) to help with the manual curation of gene families in draft genome assemblies. The program uses a pattern of short sequence motifs to identify putative genes directly from the genome sequence. Using a large gene family as a test case, Figmop was found to be more sensitive and specific than a BLAST-based approach. The visualization used allows the validation of potential genes to be carried out quickly and easily, saving hours if not days from an analysis.

Availability and implementation: Source code of Figmop is freely available for download at https://github.com/dave-the-scientist, implemented in C and Python and is supported on Linux, Unix and MacOSX.

Contact: curran.dave.m@gmail.com

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  1309 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

Full text: subscription required

How to subscribe Recommend to my Librarian

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content. subscribe or login to access all content.