{"id":239,"date":"2011-12-20T20:14:10","date_gmt":"2011-12-20T20:14:10","guid":{"rendered":"https:\/\/blogs.bmj.com\/jmg\/?p=239"},"modified":"2026-02-25T20:47:38","modified_gmt":"2026-02-25T20:47:38","slug":"a-bias-reducing-pathway-enrichment-analysis-of-genome-wide-association-data-confirmed-association-of-the-mhc-region-with-schizophrenia","status":"publish","type":"post","link":"https:\/\/blogs.bmj.com\/jmg\/2011\/12\/20\/a-bias-reducing-pathway-enrichment-analysis-of-genome-wide-association-data-confirmed-association-of-the-mhc-region-with-schizophrenia\/","title":{"rendered":"A bias-reducing pathway enrichment analysis of genome-wide association data confirmed association of the MHC region with schizophrenia (Contributed by Zhongming Zhao, Ph.D.)"},"content":{"rendered":"

Complex diseases are often caused by many genetic markers or genes, thus, pathway-based or gene-based analysis of genome-wide association study (GWAS) data becomes an important approach to studying the underlying molecular mechanisms. A critical issue in this approach is the gene length bias – long genes tend to have more SNPs investigated and, thus, have higher chance to be found significant. Jia et al. proposed a method, namely gamGWAS, which applies the generalized additive model (GAM) to effectively relieve the long gene bias. The authors successfully demonstrated gamGWAS in two schizophrenia GWAS datasets. gamGWAS is computationally efficient because it does not require genotype data or permutation of sample labels in the original GWAS data. (http:\/\/jmg.bmj.com\/cgi\/content\/abstract\/jmedgenet-2011-100397v1?papetoc<\/a> )<\/p>\n","protected":false},"excerpt":{"rendered":"

Complex diseases are often caused by many genetic markers or genes, thus, pathway-based or gene-based analysis of genome-wide association study (GWAS) data becomes an important approach to studying the underlying molecular mechanisms. A critical issue in this approach is the gene length bias – long genes tend to have more SNPs investigated and, thus, have […]<\/p>\n

Read More…<\/a><\/p>\n","protected":false},"author":123,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-239","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"\nA bias-reducing pathway enrichment analysis of genome-wide association data confirmed association of the MHC region with schizophrenia (Contributed by Zhongming Zhao, Ph.D.) - JMG Contact blog<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/blogs.bmj.com\/jmg\/2011\/12\/20\/a-bias-reducing-pathway-enrichment-analysis-of-genome-wide-association-data-confirmed-association-of-the-mhc-region-with-schizophrenia\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"A bias-reducing pathway enrichment analysis of genome-wide association data confirmed association of the MHC region with schizophrenia (Contributed by Zhongming Zhao, Ph.D.) - JMG Contact blog\" \/>\n<meta property=\"og:description\" content=\"Complex diseases are often caused by many genetic markers or genes, thus, pathway-based or gene-based analysis of genome-wide association study (GWAS) data becomes an important approach to studying the underlying molecular mechanisms. 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