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

Author:

Hahn Georg1ORCID,Lee Sanghun12,Weiss Scott T.3,Lange Christoph1

Affiliation:

1. Department of Biostatistics, T.H. Chan School of Public Health Harvard University Boston Massachusetts USA

2. Department of Medical Consilience, Graduate School Dankook University Yongin‐si South Korea

3. Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital Harvard Medical School Boston Massachusetts USA

Funder

National Human Genome Research Institute

National Heart, Lung, and Blood Institute

Publisher

Wiley

Subject

Genetics(clinical),Epidemiology

Reference24 articles.

1. Data, disease and diplomacy: GISAID's innovative contribution to global health

2. Freunde of GISAID e.V.(2020). Global initiative on sharing all influenza data—TreeTool app.https://www.gisaid.org/epiflu-applications/upcoming-features-in-v20/treetool-app/

3. Hahn G. Cho M. H. Weiss S. T. Silverman E. K. &Lange C.(2020a). Unsupervised cluster analysis of SARS‐CoV‐2 genomes indicates that recent (June 2020) cases in Beijing are from a genetic subgroup that consists of mostly European and South (east) Asian samples of which the latter are the most recent. bioRxiv:2020.06.22.165936.

4. Hahn G. Lutz S. Hecker J. Prokopenko D. Cho M. Silverman E. Weiss S. &Lange C.(2020b). Locstra: Fast analysis of regional/global stratification in whole genome sequencing (WGS) studies. Accepted for publication with Genetic Epidemiology. Preprint at bioRxiv:2020.03.06.981050.

5. Hahn G. Lutz S. &Lange C.(2020c). LocStra: Fast implementation of (Local) population stratification methods (v1.3).https://cran.r-project.org/web/packages/locStra/index.html

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