{"id":55,"date":"2019-03-04T16:08:00","date_gmt":"2019-03-04T16:08:00","guid":{"rendered":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/?p=55"},"modified":"2019-03-04T16:08:00","modified_gmt":"2019-03-04T16:08:00","slug":"wed-04-03-pgs-and-lasso-paper","status":"publish","type":"post","link":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/2019\/03\/04\/wed-04-03-pgs-and-lasso-paper\/","title":{"rendered":"Wed. 04\/03 &#8211; PGS and LASSO paper"},"content":{"rendered":"<p>please join us this coming Wednesday 6th March for the next round of the Stats reading group!<\/p>\n<p>Where: MSc student room<\/p>\n<p>When: 11am<\/p>\n<p>Presenter: Ville Karhunen<\/p>\n<p>We will be looking at the following paper<\/p>\n<p>&#8220;Polygenic scores via penalized regression on summary statistics&#8221;, Mak et al, 2017. Genetic Epidemiology,\u00a0 vol. 41 issue 6<\/p>\n<p><span style=\"font-weight: 400\">Polygenic scores (PGS) summarize the genetic contribution of a person&#8217;s genotype to a disease or phenotype. They can be used to group participants into different risk categories for diseases, and are also used as covariates in epidemiological analyses. Recently, there is much interest in methods that use published summary statistics. However there is no inherent information on linkage disequilibrium (LD) in summary statistics, so we have to use LD information available elsewhere. The authors propose a method for constructing PGS using summary statistics and a reference panel in a penalized regression framewor<\/span><span style=\"font-weight: 400\">k.<\/span><\/p>\n<p><a href=\"https:\/\/doi.org\/10.1002\/gepi.22050\">https:\/\/doi.org\/10.1002\/gepi.22050<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>please join us this coming Wednesday 6th March for the next round of the Stats reading group! Where: MSc student room When: 11am Presenter: Ville Karhunen We will be looking at the following paper &#8220;Polygenic scores via penalized regression on summary statistics&#8221;, Mak et al, 2017. Genetic Epidemiology,\u00a0 vol. 41 issue 6 Polygenic scores (PGS) [&hellip;]<\/p>\n","protected":false},"author":1190,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-55","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/posts\/55","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/users\/1190"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/comments?post=55"}],"version-history":[{"count":1,"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/posts\/55\/revisions"}],"predecessor-version":[{"id":56,"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/posts\/55\/revisions\/56"}],"wp:attachment":[{"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/media?parent=55"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/categories?post=55"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/tags?post=55"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}