{"id":2264,"date":"2022-07-21T14:07:39","date_gmt":"2022-07-21T18:07:39","guid":{"rendered":"https:\/\/www.med.unc.edu\/genetics\/raffieldlab\/?page_id=2264"},"modified":"2022-09-27T16:37:17","modified_gmt":"2022-09-27T20:37:17","slug":"publications","status":"publish","type":"page","link":"https:\/\/www.med.unc.edu\/genetics\/raffieldlab\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"<p>Dr. Raffield&#8217;s <a href=\"https:\/\/www.ncbi.nlm.nih.gov\/myncbi\/1ZgUfg92wK9Qc\/bibliography\/public\/\">complete bibliography at pubmed<\/a>.<\/p>\n<h2>New and featured publications<\/h2>\n\n<ul class=\"media alt-media\">\n        \n                            <li class=\"media-listitem\">\n                                        <div class=\"media-body\">\n                        <div class=\"caption\">\n                            <h4 class=\"media-heading\" data-shouldbe=\"h4\">                                <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/37216410\/\" rel=\"bookmark\" title=\"Canonical correlation analysis for multi-omics: Application to cross-cohort analysis\">\n                                    Canonical correlation analysis for multi-omics: Application to cross-cohort analysis<\/a>\n                                <\/h4>                            <p><p>CCA is a correlation-based method for multi-omics data which reduces the dimension of each omic assay to several orthogonal components\u2013commonly referred to as canonical variables (CVs). The widely-used SMCCA method allows effective dimension reduction and integration of multi-omics data, but suffers from potentially highly correlated CVs when applied to high-dimensional omics data. Here, we improve the statistical independence among the CVs by adopting a variation of the GS algorithm. We applied our SMCCA-GS method to proteomic and methylomic data from two cohort studies, MESA and JHS. <\/p>\n<\/p>\n                        <\/div>\n                    <\/div>\n                <\/li>\n                                \n                            <li class=\"media-listitem\">\n                                        <div class=\"media-body\">\n                        <div class=\"caption\">\n                            <h4 class=\"media-heading\" data-shouldbe=\"h4\">                                <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/34553764\/\" rel=\"bookmark\" title=\"Whole genome sequence analysis of platelet traits in the NHLBI Trans-Omics for Precision Medicine (TOPMed) initiative\">\n                                    Whole genome sequence analysis of platelet traits in the NHLBI Trans-Omics for Precision Medicine (TOPMed) initiative<\/a>\n                                <\/h4>                            <p><p>Platelets play a key role in thrombosis and hemostasis. Platelet count (PLT) and mean platelet volume (MPV) are highly heritable quantitative traits, with hundreds of genetic signals previously identified, mostly in European ancestry populations. We here utilize whole genome sequencing (WGS) from NHLBI&#8217;s Trans-Omics for Precision Medicine initiative (TOPMed) in a large multi-ethnic sample to further explore common and rare variation contributing to PLT (n = 61 200) and MPV (n = 23 485).<\/p>\n<\/p>\n                        <\/div>\n                    <\/div>\n                <\/li>\n                                <\/ul>\n    \n","protected":false},"excerpt":{"rendered":"<p>Dr. Raffield&#8217;s complete bibliography at pubmed. New and featured publications<\/p>\n","protected":false},"author":112925,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-2264","page","type-page","status-publish","hentry","odd"],"acf":[],"_links_to":[],"_links_to_target":[],"_links":{"self":[{"href":"https:\/\/www.med.unc.edu\/genetics\/raffieldlab\/wp-json\/wp\/v2\/pages\/2264","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.med.unc.edu\/genetics\/raffieldlab\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.med.unc.edu\/genetics\/raffieldlab\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.med.unc.edu\/genetics\/raffieldlab\/wp-json\/wp\/v2\/users\/112925"}],"replies":[{"embeddable":true,"href":"https:\/\/www.med.unc.edu\/genetics\/raffieldlab\/wp-json\/wp\/v2\/comments?post=2264"}],"version-history":[{"count":0,"href":"https:\/\/www.med.unc.edu\/genetics\/raffieldlab\/wp-json\/wp\/v2\/pages\/2264\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.med.unc.edu\/genetics\/raffieldlab\/wp-json\/wp\/v2\/media?parent=2264"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}