Unsupervised cluster analysis of SARS-CoV-2 genomes reflects its geographic progression and identifies distinct genetic subgroups of SARS-CoV-2 virus.

Hahn, Georg; Lee, Sanghun; Weiss, Scott T; Lange, Christoph

Hahn, Georg; Lee, Sanghun; Weiss, Scott T; Lange, Christoph.

Affiliation

Hahn G; Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA.
Lee S; Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA.
Weiss ST; Department of Medical Consilience, Graduate School, Dankook University, Yongin-si, South Korea.
Lange C; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Genet Epidemiol ; 45(3): 316-323, 2021 04.

Article in En | MEDLINE | ID: mdl-33415739

Subject(s)

COVID-19/virology; Cluster Analysis; Genome, Viral/genetics; Geographic Mapping; SARS-CoV-2/classification; SARS-CoV-2/genetics; COVID-19/epidemiology; China/epidemiology; Databases, Genetic; Europe/epidemiology; Humans; Molecular Epidemiology; North America/epidemiology; Pandemics; Phylogeny; Principal Component Analysis; Prognosis; SARS-CoV-2/isolation & purification; SARS-CoV-2/pathogenicity; Spatio-Temporal Analysis

Key words

SARS-CoV-2; clustering; covid; jaccard

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Cluster Analysis / Genome, Viral / Geographic Mapping / SARS-CoV-2 / COVID-19 Type of study: Prognostic_studies Limits: Humans Country/Region as subject: America do norte / Asia / Europa Language: En Journal: Genet Epidemiol Journal subject: EPIDEMIOLOGIA / GENETICA MEDICA Year: 2021 Type: Article Affiliation country: United States

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