Selected article for: "case study and phylogenetic analysis"

Author: Fernandes, Danrley; Kulik, Mariane G.; Machado, Diogo J. S.; Marchaukoski, Jeroniza N.; Pedrosa, Fabio O.; De Pierri, Camilla R.; Raittz, Roberto T.
Title: rSWeeP: A R/Bioconductor package deal with SWeeP sequences representation
  • Cord-id: 027ya5ky
  • Document date: 2020_9_9
  • ID: 027ya5ky
    Snippet: The rSWeeP package is an R implementation of the SWeeP model, designed to handle Big Data. rSweeP meets to the growing demand for efficient methods of heuristic representation in the field of Bioinformatics, on platforms accessible to the entire scientific community. We explored the implementation of rSWeeP using a dataset containing 31,386 viral proteomes, performing phylogenetic and principal component analysis. As a case study we analyze the viral strains closest to the SARS-CoV, responsible
    Document: The rSWeeP package is an R implementation of the SWeeP model, designed to handle Big Data. rSweeP meets to the growing demand for efficient methods of heuristic representation in the field of Bioinformatics, on platforms accessible to the entire scientific community. We explored the implementation of rSWeeP using a dataset containing 31,386 viral proteomes, performing phylogenetic and principal component analysis. As a case study we analyze the viral strains closest to the SARS-CoV, responsible for the current pandemic of COVID-19, confirming that rSWeeP can accurately classify organisms taxonomically. rSWeeP package is freely available at https://bioconductor.org/packages/release/bioc/html/rSWeeP.html.

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