https:\/\/doi.org\/10.1093\/bioinformatics\/btw052<\/a><\/p>\nPresented by: Dr Schneider-Luftman<\/p>\n
GWAS (Genome-wide association study) is a method widely used nowadays for the analysis of association between the genome and any phenotypic trait. In its classical form, it works as a “giant” univariate regression of 1 outcome against the allelic variation of all the SNPs (Single-nucleotide polymorphism) in the genome *. (*= except rare SNPs, chrm. X and Y, and other conditions….). However, there is increased interest in analysis multiple related traits together. It only makes sense to analyse them jointly, in order to increase statistical power.<\/p>\n
This paper introduce a framework to perform multi-outcome meta-analysis of GWA data, from a single of several studies. The underlying method relies on CCA (canonical correlation analysis) + shrinkage. The paper also discusses an application to several Finnish population cohorts – notably the Northern Finland Birth Cohort, very widely used at EBS – across 81 lipid NMR (nuclear magnetic resonance) measures.<\/p>\n","protected":false},"excerpt":{"rendered":"
Paper of the week: “metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis”, Cichonska et al. ,2016. Bioinformatics, Volume 32, Issue 13, Pages 1981\u20131989 https:\/\/doi.org\/10.1093\/bioinformatics\/btw052 Presented by: Dr Schneider-Luftman GWAS (Genome-wide association study) is a method widely used nowadays for the analysis of association between the genome and any phenotypic trait. […]<\/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-41","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\/41","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=41"}],"version-history":[{"count":1,"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/posts\/41\/revisions"}],"predecessor-version":[{"id":42,"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/posts\/41\/revisions\/42"}],"wp:attachment":[{"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/media?parent=41"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/categories?post=41"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/tags?post=41"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}