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GGRaSP: a R-package for selecting representative genomes using Gaussian mixture models
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6129299/ https://www.ncbi.nlm.nih.gov/pubmed/29668840 http://dx.doi.org/10.1093/bioinformatics/bty300 |
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author | Clarke, Thomas H Brinkac, Lauren M Sutton, Granger Fouts, Derrick E |
author_facet | Clarke, Thomas H Brinkac, Lauren M Sutton, Granger Fouts, Derrick E |
author_sort | Clarke, Thomas H |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6129299 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-61292992018-09-12 GGRaSP: a R-package for selecting representative genomes using Gaussian mixture models Clarke, Thomas H Brinkac, Lauren M Sutton, Granger Fouts, Derrick E Bioinformatics Applications Notes 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. Oxford University Press 2018-09-01 2018-04-14 /pmc/articles/PMC6129299/ /pubmed/29668840 http://dx.doi.org/10.1093/bioinformatics/bty300 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Clarke, Thomas H Brinkac, Lauren M Sutton, Granger Fouts, Derrick E GGRaSP: a R-package for selecting representative genomes using Gaussian mixture models |
title | GGRaSP: a R-package for selecting representative genomes using Gaussian mixture models |
title_full | GGRaSP: a R-package for selecting representative genomes using Gaussian mixture models |
title_fullStr | GGRaSP: a R-package for selecting representative genomes using Gaussian mixture models |
title_full_unstemmed | GGRaSP: a R-package for selecting representative genomes using Gaussian mixture models |
title_short | GGRaSP: a R-package for selecting representative genomes using Gaussian mixture models |
title_sort | ggrasp: a r-package for selecting representative genomes using gaussian mixture models |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6129299/ https://www.ncbi.nlm.nih.gov/pubmed/29668840 http://dx.doi.org/10.1093/bioinformatics/bty300 |
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