{"id":4197,"date":"2015-06-16T09:57:10","date_gmt":"2015-06-16T07:57:10","guid":{"rendered":"http:\/\/news.embl.de\/?p=4197"},"modified":"2024-11-29T16:53:03","modified_gmt":"2024-11-29T15:53:03","slug":"1506-genome-analysis","status":"publish","type":"post","link":"https:\/\/www.embl.org\/news\/science\/1506-genome-analysis\/","title":{"rendered":"Large-scale genetic analysis made easier"},"content":{"rendered":"\n<p>Researchers at EMBL-EBI have developed a new approach to studying the effect of multiple genetic variations on different traits. The new algorithm, <a href=\"http:\/\/dx.doi.org\/10.1038\/nmeth.3439\">published in <em>Nature Methods<\/em><\/a>, makes it possible to perform genetic analysis of up to 500,000 individuals \u2013 and many traits \u2013 at the same time.<\/p>\n\n\n\n<p>The relationship between genes and specific traits is more complicated than simple one-to-one relationships between genes and diseases. Genome-wide association studies (GWAS) show that many genetic factors are at play for any given trait, but scientists are just beginning to explore how, specifically, genetic variations affect health and disease. Two major statistical challenges to finding these connections involve analysing associations between many different genetic variants and multiple traits, and making the best use of data from large cohorts that include hundreds of thousands of individuals.<\/p>\n\n\n\n<blockquote class=\"vf-blockquote\"><p>Our algorithm can be used to study up to half a million individuals \u2013 that hasn\u2019t been possible until now.<\/p><\/blockquote>\n\n\n\n<p>\u201cIt is very challenging to identify genetic variants that underlie phenotypes, or traits, and usually we do this by analysing each phenotype and each variant one by one,\u201d explains <a href=\"http:\/\/www.ebi.ac.uk\/about\/people\/oliver-stegle\" target=\"_blank\" rel=\"noopener noreferrer\">Oliver Stegle, research group leader<\/a> at EMBL-EBI. \u201cBut the simple models we use to do this are too simplistic to uncover the complex dependencies between sets of genetic variants and disease phenotypes.\u201d<\/p>\n\n\n\n<p>Complex models that let you look at the combined action of many different variants have, until now, involved so much computation that it would take a year to run a single complex query.&nbsp;\u201cThe breakthrough here is that we\u2019ve made it possible to perform an integrative analysis involving many variants and phenotypes at the same speed as current approaches,\u201d says Stegle.<\/p>\n\n\n\n<p>The researchers tested their algorithm on data from two studies from public repositories, and compared the results with existing state-of-the-art tools. Their study of four lipid-related traits (LDL and HDL cholesterol levels, C-reactive protein, triglycerides) proved that the new method is substantially faster, and can explain a larger proportion of these traits in terms of the genetics that drive them.<\/p>\n\n\n\n<p>\u201cWe wanted to be able to look at these questions from both directions,\u201d says Stegle. \u201cOn the one hand, we want to look at all the variants in a single gene that may be involved in the regulation of one particular lipid trait. On the other, we want to look at the combined effect across larger sets of lipid levels, for example to find out something about lipid regulation in general.\u201d<\/p>\n\n\n\n<blockquote class=\"vf-blockquote\"><p>The new algorithm provides much-needed methods for genomics, making large-scale, complex analysis a manageable and practical endeavour.<\/p><\/blockquote>\n\n\n\n<p>Using the new method, GWAS researchers can explore several variants of a gene at once while comparing them with several related phenotypes. This makes it much easier to pinpoint which genes or \u2013 or locations on genes \u2013 are involved in a particular function, such as lipid regulation.<\/p>\n\n\n\n<p>\u201cWhat\u2019s important about this work is that it improves statistical power and provides the tools people need to analyse multiple traits in very large cohorts,\u201d says Stegle. \u201cOur algorithm can be used to study up to half a million individuals \u2013 that hasn\u2019t been possible until now.\u201d<\/p>\n\n\n\n<p>\u201cCurrently, people are either using multiple variant methods on one phentoype, or multiple phenotype methods but looking at just one variant at a time. Oliver\u2019s new scheme is a real advance because it lets you do both at the same time, and is scalable to be used on the very large cohorts we are starting to see in initiatives like the UK BioBank,\u201d says <a href=\"http:\/\/www.ebi.ac.uk\/about\/people\/ewan-birney\" target=\"_blank\" rel=\"noopener noreferrer\">Ewan Birney, Associate Director<\/a> at EMBL-EBI.<\/p>\n\n\n\n<p>The new algorithm provides much-needed methods for genomics, making large-scale, complex analysis a manageable and practical endeavour.<\/p>\n\n\n\n<p>\u201cOur method, which we call mSet, provides a principled approach to testing for statistical relationships between multiple genetic variants and groups of traits. These methods will help researchers determine which specific aspects of our biology are inherited, and uncover new insights into the genetics behind our countless biological processes.\u201d<\/p>\n\n\n\n<p><em>This post was originally published on <a href=\"https:\/\/www.ebi.ac.uk\/about\/news\/press-releases\/gwas-analysis-made-easier\" target=\"_blank\" rel=\"canonical nofollow noopener noreferrer\" data-href=\"https:\/\/www.ebi.ac.uk\/about\/news\/press-releases\/gwas-analysis-made-easier\">EMBL-EBI News.<\/a><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Researchers at EMBL-EBI speed up complex GWAS analyses with new method and algorithm.<\/p>\n","protected":false},"author":13,"featured_media":4265,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[2,17591],"tags":[28,368,36,41,69],"embl_taxonomy":[],"class_list":["post-4197","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-science","category-science-technology","tag-bioinformatics","tag-birney","tag-embl-ebi","tag-genetics","tag-methods"],"acf":{"article_intro":"<p>Researchers at EMBL-EBI speed up complex GWAS analyses with new method and algorithm.<\/p>\n","related_links":[{"link_description":"LIMIX: a flexible, efficient linear mixed model library where the new algorithm is implemented","link_url":"http:\/\/github.com\/PMBio\/limix"},{"link_description":"This article first appeared as a press release on the EMBL-EBI website, 15 June 2015","link_url":"http:\/\/www.ebi.ac.uk\/about\/news\/press-releases\/gwas-analysis-made-easier"}],"article_sources":[{"source_description":"<p>Casale FP, <em>et al. Nature Methods<\/em> (in press). Published online 15 June\u00a02015.\u00a0DOI: 10.1038\/nmeth.3439<\/p>\n","source_link_url":"http:\/\/dx.doi.org\/10.1038\/nmeth.3439"}],"vf_locked":false,"featured":false,"color":"#007B53"},"embl_taxonomy_terms":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Large-scale genetic analysis made easier | EMBL<\/title>\n<meta name=\"description\" content=\"New methods developed at EMBL-EBI help perform genetic analysis of up to 500,000 individuals and many traits at the same time.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.embl.org\/news\/science\/1506-genome-analysis\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Large-scale genetic analysis made easier | EMBL\" \/>\n<meta property=\"og:description\" content=\"New methods developed at EMBL-EBI help perform genetic analysis of up to 500,000 individuals and many traits at the same time.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.embl.org\/news\/science\/1506-genome-analysis\/\" \/>\n<meta property=\"og:site_name\" content=\"EMBL\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/embl.org\/\" \/>\n<meta property=\"article:author\" content=\"www.facebook.com\/EMBLEBI\" \/>\n<meta property=\"article:published_time\" content=\"2015-06-16T07:57:10+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-11-29T15:53:03+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.embl.org\/news\/wp-content\/uploads\/2015\/06\/mSet_news_EMBL1.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"620\" \/>\n\t<meta property=\"og:image:height\" content=\"465\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Mary Todd Bergman\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@EMBLEBI\" \/>\n<meta name=\"twitter:site\" content=\"@embl\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Mary Todd Bergman\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"3 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"NewsArticle\",\"@id\":\"https:\/\/www.embl.org\/news\/science\/1506-genome-analysis\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.embl.org\/news\/science\/1506-genome-analysis\/\"},\"author\":{\"name\":\"Mary Todd Bergman\",\"@id\":\"https:\/\/www.embl.org\/news\/#\/schema\/person\/052a43af2beb3860bffa67c0f0474875\"},\"headline\":\"Large-scale genetic analysis made easier\",\"datePublished\":\"2015-06-16T07:57:10+00:00\",\"dateModified\":\"2024-11-29T15:53:03+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.embl.org\/news\/science\/1506-genome-analysis\/\"},\"wordCount\":665,\"publisher\":{\"@id\":\"https:\/\/www.embl.org\/news\/#organization\"},\"image\":{\"@id\":\"https:\/\/www.embl.org\/news\/science\/1506-genome-analysis\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.embl.org\/news\/wp-content\/uploads\/2015\/06\/mSet_news_EMBL1.jpg\",\"keywords\":[\"bioinformatics\",\"birney\",\"embl-ebi\",\"genetics\",\"methods\"],\"articleSection\":[\"Science\",\"Science &amp; 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