Tracing Sub-Structure in the European American Population with PCA-Informative Markers
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{"title"=>"Tracing sub-structure in the European American population with PCA-informative markers", "type"=>"journal", "authors"=>[{"first_name"=>"Peristera", "last_name"=>"Paschou", "scopus_author_id"=>"22136326700"}, {"first_name"=>"Petros", "last_name"=>"Drineas", "scopus_author_id"=>"6602866337"}, {"first_name"=>"Jamey", "last_name"=>"Lewis", "scopus_author_id"=>"55483993200"}, {"first_name"=>"Caroline M.", "last_name"=>"Nievergelt", "scopus_author_id"=>"6602829768"}, {"first_name"=>"Deborah A.", "last_name"=>"Nickerson", "scopus_author_id"=>"7005755969"}, {"first_name"=>"Joshua D.", "last_name"=>"Smith", "scopus_author_id"=>"56538933200"}, {"first_name"=>"Paul M.", "last_name"=>"Ridker", "scopus_author_id"=>"36039269800"}, {"first_name"=>"Daniel I.", "last_name"=>"Chasman", "scopus_author_id"=>"6701612213"}, {"first_name"=>"Ronald M.", "last_name"=>"Krauss", "scopus_author_id"=>"7103124166"}, {"first_name"=>"Elad", "last_name"=>"Ziv", "scopus_author_id"=>"7004657353"}], "year"=>2008, "source"=>"PLoS Genetics", "identifiers"=>{"issn"=>"15537390", "pui"=>"352076474", "doi"=>"10.1371/journal.pgen.1000114", "sgr"=>"48249148358", "scopus"=>"2-s2.0-48249148358", "isbn"=>"1553-7404 (Electronic)", "pmid"=>"18797516"}, "id"=>"676165e6-e21f-34b3-b966-c5e8fdeffa3c", "abstract"=>"Genetic structure in the European American population reflects waves of migration and recent gene flow among different populations. This complex structure can introduce bias in genetic association studies. Using Principal Components Analysis (PCA), we analyze the structure of two independent European American datasets (1,521 individuals-307,315 autosomal SNPs). Individual variation lies across a continuum with some individuals showing high degrees of admixture with non-European populations, as demonstrated through joint analysis with HapMap data. The CEPH Europeans only represent a small fraction of the variation encountered in the larger European American datasets we studied. We interpret the first eigenvector of this data as correlated with ancestry, and we apply an algorithm that we have previously described to select PCA-informative markers (PCAIMs) that can reproduce this structure. Importantly, we develop a novel method that can remove redundancy from the selected SNP panels and show that we can effectively remove correlated markers, thus increasing genotyping savings. Only 150-200 PCAIMs suffice to accurately predict fine structure in European American datasets, as identified by PCA. Simulating association studies, we couple our method with a PCA-based stratification correction tool and demonstrate that a small number of PCAIMs can efficiently remove false correlations with almost no loss in power. The structure informative SNPs that we propose are an important resource for genetic association studies of European Americans. Furthermore, our redundancy removal algorithm can be applied on sets of ancestry informative markers selected with any method in order to select the most uncorrelated SNPs, and significantly decreases genotyping costs.", "link"=>"http://www.mendeley.com/research/tracing-substructure-european-american-population-pcainformative-markers", "reader_count"=>98, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>7, "Librarian"=>1, "Researcher"=>34, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>24, "Student > Postgraduate"=>6, "Student > Master"=>9, "Other"=>1, "Student > Bachelor"=>3, "Lecturer"=>1, "Professor"=>8}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>7, "Librarian"=>1, "Researcher"=>34, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>24, "Student > Postgraduate"=>6, "Student > Master"=>9, "Other"=>1, "Student > Bachelor"=>3, "Lecturer"=>1, "Professor"=>8}, "reader_count_by_subject_area"=>{"Engineering"=>2, "Unspecified"=>6, "Biochemistry, Genetics and Molecular Biology"=>7, "Mathematics"=>5, "Agricultural and Biological Sciences"=>62, "Medicine and Dentistry"=>8, "Neuroscience"=>1, "Social Sciences"=>2, "Computer Science"=>4, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>2}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>8}, "Neuroscience"=>{"Neuroscience"=>1}, "Social Sciences"=>{"Social Sciences"=>2}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>62}, "Computer Science"=>{"Computer Science"=>4}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>7}, "Mathematics"=>{"Mathematics"=>5}, "Unspecified"=>{"Unspecified"=>6}}, "reader_count_by_country"=>{"Uruguay"=>2, "United States"=>7, "Philippines"=>1, "United Kingdom"=>1, "Switzerland"=>2, "Spain"=>1, "Austria"=>1, "Sweden"=>1, "Netherlands"=>1, "Norway"=>1, "Brazil"=>1, "France"=>2, "Australia"=>1}, "group_count"=>4}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/457310", "https://ndownloader.figshare.com/files/457388", "https://ndownloader.figshare.com/files/457454", "https://ndownloader.figshare.com/files/457500", "https://ndownloader.figshare.com/files/457661", "https://ndownloader.figshare.com/files/457707", "https://ndownloader.figshare.com/files/457766", "https://ndownloader.figshare.com/files/457830"], "description"=>"<div><p>Genetic structure in the European American population reflects waves of migration and recent gene flow among different populations. This complex structure can introduce bias in genetic association studies. Using Principal Components Analysis (PCA), we analyze the structure of two independent European American datasets (1,521 individuals–307,315 autosomal SNPs). Individual variation lies across a continuum with some individuals showing high degrees of admixture with non-European populations, as demonstrated through joint analysis with HapMap data. The CEPH Europeans only represent a small fraction of the variation encountered in the larger European American datasets we studied. We interpret the first eigenvector of this data as correlated with ancestry, and we apply an algorithm that we have previously described to select PCA-informative markers (PCAIMs) that can reproduce this structure. Importantly, we develop a novel method that can remove redundancy from the selected SNP panels and show that we can effectively remove correlated markers, thus increasing genotyping savings. Only 150–200 PCAIMs suffice to accurately predict fine structure in European American datasets, as identified by PCA. Simulating association studies, we couple our method with a PCA-based stratification correction tool and demonstrate that a small number of PCAIMs can efficiently remove false correlations with almost no loss in power. The structure informative SNPs that we propose are an important resource for genetic association studies of European Americans. Furthermore, our redundancy removal algorithm can be applied on sets of ancestry informative markers selected with any method in order to select the most uncorrelated SNPs, and significantly decreases genotyping costs.</p></div>", "links"=>[], "tags"=>["tracing", "sub-structure", "european", "american", "pca-informative", "markers"], "article_id"=>150078, "categories"=>["Cell Biology", "Genetics", "Cancer"], "users"=>["Peristera Paschou", "Petros Drineas", "Jamey Lewis", "Caroline M. Nievergelt", "Deborah A. Nickerson", "Joshua D. Smith", "Paul M. Ridker", "Daniel I. Chasman", "Ronald M. Krauss", "Elad Ziv"], "doi"=>["https://dx.doi.org/10.1371/journal.pgen.1000114.s001", "https://dx.doi.org/10.1371/journal.pgen.1000114.s002", "https://dx.doi.org/10.1371/journal.pgen.1000114.s003", "https://dx.doi.org/10.1371/journal.pgen.1000114.s004", "https://dx.doi.org/10.1371/journal.pgen.1000114.s005", "https://dx.doi.org/10.1371/journal.pgen.1000114.s007", "https://dx.doi.org/10.1371/journal.pgen.1000114.s008", "https://dx.doi.org/10.1371/journal.pgen.1000114.s006"], "stats"=>{"downloads"=>36, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Tracing_Sub_Structure_in_the_European_American_Population_with_PCA_Informative_Markers/150078", "title"=>"Tracing Sub-Structure in the European American Population with PCA-Informative Markers", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2008-07-04 00:01:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/927796"], "description"=>"<p>There are numerous highly correlated pairs. However, after our redundancy removal step, in the retained 500 PCAIMs there was no pair (in any of the three datasets) with an <i>r</i><sup>2</sup> value above 0.2 and only three pairs in the CORIELL dataset with an <i>r</i><sup>2</sup> value between 0.1 and 0.2.</p>", "links"=>[], "tags"=>["pairs", "3000", "pcaims", "coriell", "chori"], "article_id"=>598234, "categories"=>["Plant Biology", "Genetics", "Cancer"], "users"=>["Peristera Paschou", "Petros Drineas", "Jamey Lewis", "Caroline M. Nievergelt", "Deborah A. Nickerson", "Joshua D. Smith", "Paul M. Ridker", "Daniel I. Chasman", "Ronald M. Krauss", "Elad Ziv"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000114.t001", "stats"=>{"downloads"=>1, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Number_of_pairs_of_the_top_3000_PCAIMs_with_r_2_values_above_0_1_in_the_CORIELL_dataset_the_CHORI_dataset_and_the_joint_CORIELL_and_CHORI_dataset_/598234", "title"=>"Number of pairs of the top 3000 PCAIMs with <i>r</i><sup>2</sup> values above 0.1 in the CORIELL dataset, the CHORI dataset, and the joint CORIELL and CHORI dataset.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2008-07-04 02:17:14"}
  • {"files"=>["https://ndownloader.figshare.com/files/927559"], "description"=>"<p>(A) Raster plot of the top 500 PCAIMs for all 1497 subjects in the CHORI and CORIELL datasets, after removing redundant SNPs from the top 3000 PCAIMs using the greedy <i>QR</i> method. Red and green denotes heterozygotes while homozygotes are black. Individuals are sorted according to their coordinates in the first eigenSNP. (B) The first eigenSNP of the matrix in (A). This vector corresponds to our prediction of ancestry. (C) The first eigenSNP of the matrix of the CHORI and CORIELL subjects on all 307,315 SNPs. This vector is interpreted as “true” ancestry for the individuals. Notice that the two vectors are highly correlated. (D) Pearson correlation coefficient between predicted ancestry and “true” ancestry for the 1497 subjects of European American ancestry using panels of PCAIMs, non-redundant PCAIMs, and random SNPs. Clearly, non-redundant PCAIMs are very good predictors of ancestry.</p>", "links"=>[], "tags"=>["extracts", "genotype"], "article_id"=>598005, "categories"=>["Plant Biology", "Genetics", "Cancer"], "users"=>["Peristera Paschou", "Petros Drineas", "Jamey Lewis", "Caroline M. Nievergelt", "Deborah A. Nickerson", "Joshua D. Smith", "Paul M. Ridker", "Daniel I. Chasman", "Ronald M. Krauss", "Elad Ziv"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000114.g004", "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_PCA_extracts_meaningful_information_from_genotype_data_/598005", "title"=>"PCA extracts meaningful information from genotype data.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-07-04 02:13:25"}
  • {"files"=>["https://ndownloader.figshare.com/files/927132"], "description"=>"<p>(A) Histogram of the first eigenSNP of the CORIELL dataset. (B) The singular values corresponding to the first up to the tenth eigenSNP of the CORIELL dataset. (C) The results of the permutation test to determine the significance of the principal components of the CORIELL dataset. Higher values on the <i>y</i>-axis correspond to principal components containing significantly more structure than a random component would. (D) Histogram of the first eigenSNP of the CHORI dataset. (E) The singular values corresponding to the first up to the tenth eigenSNP of the CHORI dataset. (F) The results of the permutation test to determine the significance of the principal components of the CHORI dataset.</p>", "links"=>[], "tags"=>["components", "chori", "coriell"], "article_id"=>597570, "categories"=>["Plant Biology", "Genetics", "Cancer"], "users"=>["Peristera Paschou", "Petros Drineas", "Jamey Lewis", "Caroline M. Nievergelt", "Deborah A. Nickerson", "Joshua D. Smith", "Paul M. Ridker", "Daniel I. Chasman", "Ronald M. Krauss", "Elad Ziv"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000114.g001", "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Singular_values_and_test_of_significance_of_principal_components_in_the_CHORI_and_CORIELL_datasets_/597570", "title"=>"Singular values and test of significance of principal components in the CHORI and CORIELL datasets.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-07-04 02:06:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/927402"], "description"=>"<p>(A) Pearson correlation coefficient between predicted ancestry and “true” ancestry for the 539 subjects in the CORIELL dataset. (B) Pearson correlation coefficient between predicted ancestry and “true” ancestry for the 958 subjects in the CHORI dataset. (For random SNPs, the average over 20 experiments is reported).</p>", "links"=>[], "tags"=>["pcaims", "predictors"], "article_id"=>597839, "categories"=>["Plant Biology", "Genetics", "Cancer"], "users"=>["Peristera Paschou", "Petros Drineas", "Jamey Lewis", "Caroline M. Nievergelt", "Deborah A. Nickerson", "Joshua D. Smith", "Paul M. Ridker", "Daniel I. Chasman", "Ronald M. Krauss", "Elad Ziv"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000114.g003", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Non_redundant_PCAIMs_are_very_good_predictors_of_ancestry_/597839", "title"=>"Non-redundant PCAIMs are very good predictors of ancestry.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-07-04 02:10:39"}
  • {"files"=>["https://ndownloader.figshare.com/files/927664"], "description"=>"<p>(A) Pearson correlation coefficient between ancestry prediction of CHORI subjects using SNPs selected in the CORIELL dataset, and “true” ancestry of the CHORI subjects. (B) Pearson correlation coefficient between ancestry prediction of CORIELL subjects using SNPs selected in the CHORI dataset, and “true” ancestry of the CORIELL subjects. (C) Split of the CHORI dataset in 50% training and 50% test set. Pearson correlation coefficient between ancestry prediction of test set subjects using SNPs selected in the training set, and “true” ancestry of the test set subjects. Results are reported over 20 splits.</p>", "links"=>[], "tags"=>["panels", "pcaims", "ancestry", "european"], "article_id"=>598108, "categories"=>["Plant Biology", "Genetics", "Cancer"], "users"=>["Peristera Paschou", "Petros Drineas", "Jamey Lewis", "Caroline M. Nievergelt", "Deborah A. Nickerson", "Joshua D. Smith", "Paul M. Ridker", "Daniel I. Chasman", "Ronald M. Krauss", "Elad Ziv"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000114.g005", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Cross_validation_of_panels_of_PCAIMs_for_ancestry_prediction_in_European_Americans_/598108", "title"=>"Cross-validation of panels of PCAIMs for ancestry prediction in European Americans.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-07-04 02:15:08"}
  • {"files"=>["https://ndownloader.figshare.com/files/927241"], "description"=>"<p>Notice that the individuals of European American ancestry lie along a line with very little deviations toward the Asian and African populations (14 outliers have been removed from this analysis, as described in <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1000114#s2\" target=\"_blank\">Methods</a>).</p>", "links"=>[], "tags"=>["958", "539", "270", "hapmap", "individuals"], "article_id"=>597679, "categories"=>["Plant Biology", "Genetics", "Cancer"], "users"=>["Peristera Paschou", "Petros Drineas", "Jamey Lewis", "Caroline M. Nievergelt", "Deborah A. Nickerson", "Joshua D. Smith", "Paul M. Ridker", "Daniel I. Chasman", "Ronald M. Krauss", "Elad Ziv"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000114.g002", "stats"=>{"downloads"=>0, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Projection_of_958_CHORI_539_CORIELL_and_270_HapMap_individuals_on_their_first_second_and_third_eigenSNPs_/597679", "title"=>"Projection of 958 CHORI, 539 CORIELL, and 270 HapMap individuals on their first, second, and third eigenSNPs.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-07-04 02:07:59"}
  • {"files"=>["https://ndownloader.figshare.com/files/927751"], "description"=>"<p>The first column shows the proportion of random, stratified, and causal SNPs that are identified as causal using the Armitage's trend test with a cut-off <i>p</i>-value of 10<sup>−4</sup>. The remaining columns show the respective proportions after stratification correction using 100, 200, and 400 PCAIMs.</p>", "links"=>[], "tags"=>["pcaims", "stratification", "correction", "conjuction"], "article_id"=>598191, "categories"=>["Plant Biology", "Genetics", "Cancer"], "users"=>["Peristera Paschou", "Petros Drineas", "Jamey Lewis", "Caroline M. Nievergelt", "Deborah A. Nickerson", "Joshua D. Smith", "Paul M. Ridker", "Daniel I. Chasman", "Ronald M. Krauss", "Elad Ziv"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000114.t002", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Using_PCAIMs_for_stratification_correction_in_conjuction_with_EIGENSTRAT_s_algorithm_/598191", "title"=>"Using PCAIMs for stratification correction in conjuction with EIGENSTRAT's algorithm.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2008-07-04 02:16:31"}

PMC Usage Stats | Further Information

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Relative Metric

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