Using Network Methodology to Infer Population Substructure
Publication Date
June 22, 2015
Journal
PLOS ONE
Authors
Dmitry Prokopenko, Julian Hecker, Edwin Silverman, Markus M. Nöthen, et al
Volume
10
Issue
6
Pages
e0130708
DOI
https://dx.plos.org/10.1371/journal.pone.0130708
Publisher URL
http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0130708
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/26098940
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4476755
Europe PMC
http://europepmc.org/abstract/MED/26098940
Scopus
84939127783
Mendeley
http://www.mendeley.com/research/using-network-methodology-infer-population-substructure
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Mendeley | Further Information

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Scopus | Further Information

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Figshare

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  • {"files"=>["https://ndownloader.figshare.com/files/2129865"], "description"=>"<p>PUR—Puerto Rican, CLM—Colombian, MXL–Mexican</p><p>Contingency table for American subpopulations, rows correspond to detected communities, columns to actual subpopulations.</p>", "links"=>[], "tags"=>["type 1 error", "population structures", "1000 Genomes data", "population substructure", "admixture", "1000 genomes project", "Network Methodology", "predefined pairwise similarity measure", "Association Studies", "method", "population structure", "eigenstrat", "component analysis", "novel visualization technique", "community detection algorithms", "network approach", "Infer Population Substructure", "population stratification", "triad"], "article_id"=>1457435, "categories"=>["Uncategorised"], "users"=>["Dmitry Prokopenko", "Julian Hecker", "Edwin Silverman", "Markus M. Nöthen", "Matthias Schmid", "Christoph Lange", "Heide Loehlein Fier"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130708.t003", "stats"=>{"downloads"=>6, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Contingency_table_for_American_subpopulations_rows_correspond_to_detected_communities_columns_to_actual_subpopulations_/1457435", "title"=>"Contingency table for American subpopulations, rows correspond to detected communities, columns to actual subpopulations.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-06-22 04:09:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/2129866"], "description"=>"<p>YRI—Yoruba in Nigeria, LWK—Luhya in Kenia, ASW—African ancestry in Southwest US</p><p>Contingency table for African subpopulations, rows correspond to detected communities, columns to actual subpopulations.</p>", "links"=>[], "tags"=>["type 1 error", "population structures", "1000 Genomes data", "population substructure", "admixture", "1000 genomes project", "Network Methodology", "predefined pairwise similarity measure", "Association Studies", "method", "population structure", "eigenstrat", "component analysis", "novel visualization technique", "community detection algorithms", "network approach", "Infer Population Substructure", "population stratification", "triad"], "article_id"=>1457436, "categories"=>["Uncategorised"], "users"=>["Dmitry Prokopenko", "Julian Hecker", "Edwin Silverman", "Markus M. Nöthen", "Matthias Schmid", "Christoph Lange", "Heide Loehlein Fier"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130708.t004", "stats"=>{"downloads"=>5, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Contingency_table_for_African_subpopulations_rows_correspond_to_detected_communities_columns_to_actual_subpopulations_/1457436", "title"=>"Contingency table for African subpopulations, rows correspond to detected communities, columns to actual subpopulations.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-06-22 04:09:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/2129867"], "description"=>"<p>CHS—Southern Han Chinese, CHB—Han Chinese in Beijing, JPT—Japanese in Tokyo</p><p>Contingency table for Asian subpopulations, rows correspond to detected communities, columns to actual subpopulations.</p>", "links"=>[], "tags"=>["type 1 error", "population structures", "1000 Genomes data", "population substructure", "admixture", "1000 genomes project", "Network Methodology", "predefined pairwise similarity measure", "Association Studies", "method", "population structure", "eigenstrat", "component analysis", "novel visualization technique", "community detection algorithms", "network approach", "Infer Population Substructure", "population stratification", "triad"], "article_id"=>1457437, "categories"=>["Uncategorised"], "users"=>["Dmitry Prokopenko", "Julian Hecker", "Edwin Silverman", "Markus M. Nöthen", "Matthias Schmid", "Christoph Lange", "Heide Loehlein Fier"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130708.t005", "stats"=>{"downloads"=>9, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Contingency_table_for_Asian_subpopulations_rows_correspond_to_detected_communities_columns_to_actual_subpopulations_/1457437", "title"=>"Contingency table for Asian subpopulations, rows correspond to detected communities, columns to actual subpopulations.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-06-22 04:09:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/2129868"], "description"=>"<p>GBR—British in England and Scotland, FIN—Finnish, IBS—Iberian in Spain, CEU—Utah residents with Northern and Western European ancestry, TSI—Toscani in Italy</p><p>Contingency table for European subpopulations, rows correspond to detected communities, columns to actual subpopulations.</p>", "links"=>[], "tags"=>["type 1 error", "population structures", "1000 Genomes data", "population substructure", "admixture", "1000 genomes project", "Network Methodology", "predefined pairwise similarity measure", "Association Studies", "method", "population structure", "eigenstrat", "component analysis", "novel visualization technique", "community detection algorithms", "network approach", "Infer Population Substructure", "population stratification", "triad"], "article_id"=>1457438, "categories"=>["Uncategorised"], "users"=>["Dmitry Prokopenko", "Julian Hecker", "Edwin Silverman", "Markus M. Nöthen", "Matthias Schmid", "Christoph Lange", "Heide Loehlein Fier"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130708.t006", "stats"=>{"downloads"=>8, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Contingency_table_for_European_subpopulations_rows_correspond_to_detected_communities_columns_to_actual_subpopulations_/1457438", "title"=>"Contingency table for European subpopulations, rows correspond to detected communities, columns to actual subpopulations.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-06-22 04:09:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/2129869"], "description"=>"<p>The values in the table represent the proportions of SNPs (averaged over 10 replications) found to be significant. The significance level was set to 0.0001. The results are present for 4 scenarios, which are described in the section: \"Evaluation via simulated association studies \".</p><p>* For these methods in the scenario with 3 underlying discrete subpopulations we took 2 principal components and 2 ancestry estimates, as recommended by the authors.</p><p>Average proportions of significant SNPs in the simulation study.</p>", "links"=>[], "tags"=>["type 1 error", "population structures", "1000 Genomes data", "population substructure", "admixture", "1000 genomes project", "Network Methodology", "predefined pairwise similarity measure", "Association Studies", "method", "population structure", "eigenstrat", "component analysis", "novel visualization technique", "community detection algorithms", "network approach", "Infer Population Substructure", "population stratification", "triad"], "article_id"=>1457439, "categories"=>["Uncategorised"], "users"=>["Dmitry Prokopenko", "Julian Hecker", "Edwin Silverman", "Markus M. Nöthen", "Matthias Schmid", "Christoph Lange", "Heide Loehlein Fier"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130708.t007", "stats"=>{"downloads"=>6, "page_views"=>16, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Average_proportions_of_significant_SNPs_in_the_simulation_study_/1457439", "title"=>"Average proportions of significant SNPs in the simulation study.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-06-22 04:09:07"}

PMC Usage Stats | Further Information

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  • {"unique-ip"=>"1", "full-text"=>"2", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2016", "month"=>"4"}
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  • {"unique-ip"=>"5", "full-text"=>"4", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"3"}
  • {"unique-ip"=>"3", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2019", "month"=>"1"}
  • {"unique-ip"=>"10", "full-text"=>"11", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
  • {"unique-ip"=>"5", "full-text"=>"4", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"4", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
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  • {"unique-ip"=>"5", "full-text"=>"3", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"6", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
  • {"unique-ip"=>"4", "full-text"=>"6", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
  • {"unique-ip"=>"4", "full-text"=>"5", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"8"}
  • {"unique-ip"=>"2", "full-text"=>"3", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"8", "full-text"=>"10", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
  • {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}
  • {"unique-ip"=>"10", "full-text"=>"12", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"8"}

Relative Metric

{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}
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