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GGRaSP: a R-package for selecting representative genomes using Gaussian mixture models
Author(s) -
Thomas H. Clarke,
Lauren Brinkac,
Granger Sutton,
Derrick E. Fouts
Publication year - 2018
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bty300
Subject(s) - genome , cluster analysis , selection (genetic algorithm) , computational biology , computer science , biology , bacterial genome size , r package , genomics , data mining , genetics , artificial intelligence , gene , computational science
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.

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