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GGRaSP: a R-package for selecting representative genomes using Gaussian mixture models.
Clarke, Thomas H; Brinkac, Lauren M; Sutton, Granger; Fouts, Derrick E.
Afiliação
  • Clarke TH; J. Craig Venter Institute, Rockville, MD, USA.
  • Brinkac LM; J. Craig Venter Institute, Rockville, MD, USA.
  • Sutton G; Department of Biotechnology and Food Technology, Durban University of Technology, Durban, South Africa.
  • Fouts DE; J. Craig Venter Institute, Rockville, MD, USA.
Bioinformatics ; 34(17): 3032-3034, 2018 09 01.
Article em En | MEDLINE | ID: mdl-29668840
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. 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. Availability and implementaion: GGRaSP is available at https://github.com/JCVenterInstitute/ggrasp/. Supplementary information: Supplementary data are available at Bioinformatics online.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Genoma Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Genoma Idioma: En Ano de publicação: 2018 Tipo de documento: Article