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GGRaSP: a R-package for selecting representative genomes using Gaussian mixture models.

Authors :
Clarke TH
Brinkac LM
Sutton G
Fouts DE
Source :
Bioinformatics (Oxford, England) [Bioinformatics] 2018 Sep 01; Vol. 34 (17), pp. 3032-3034.
Publication Year :
2018

Abstract

Motivation: The vast number of available sequenced bacterial genomes occasionally exceeds the facilities of comparative genomic methods or is dominated by a single outbreak strain, and thus a diverse and representative subset is required. Generation of the reduced subset currently requires a priori supervised clustering and sequence-only selection of medoid genomic sequences, independent of any additional genome metrics or strain attributes.<br />Results: The Gaussian Genome Representative Selector with Prioritization (GGRaSP) R-package described below generates a reduced subset of genomes that prioritizes maintaining genomes of interest to the user as well as minimizing the loss of genetic variation. The package also allows for unsupervised clustering by modeling the genomic relationships using a Gaussian mixture model to select an appropriate cluster threshold. We demonstrate the capabilities of GGRaSP by generating a reduced list of 315 genomes from a genomic dataset of 4600 Escherichia coli genomes, prioritizing selection by type strain and by genome completeness.<br />Availability and Implementaion: GGRaSP is available at https://github.com/JCVenterInstitute/ggrasp/.<br />Supplementary Information: Supplementary data are available at Bioinformatics online.

Details

Language :
English
ISSN :
1367-4811
Volume :
34
Issue :
17
Database :
MEDLINE
Journal :
Bioinformatics (Oxford, England)
Publication Type :
Academic Journal
Accession number :
29668840
Full Text :
https://doi.org/10.1093/bioinformatics/bty300