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10.1038/ng.610 http://scihub22266oqcxt.onion/10.1038/ng.610 C4615599!4615599 !20562874     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=20562874 &cmd=llinks): Failed to open stream: HTTP request failed! 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Estimation of effect size distribution from genome-wide association studies and implications for future discoveries |pdf=|usr=}}{{20562874 }} gab.com Text Estimation of effect size distribution from genome-wide association studies and implications for future discoveries JO: Nat Genet http://www.kidney.de/pget.php?&tw=1&pmid=20562874 #FOAvip We report a set of tools to estimate the number of susceptibility loci and the distribution of their effect sizes for a trait on the basis of discoveries from existing genome-wide association studies (GWASs). We propose statistical power calculations for future GWASs using estimated distributions of effect sizes. Using reported GWAS findings for height, Crohn's disease and breast, prostate and colorectal (BPC) cancers, we determine that each of these traits is likely to harbor additional loci within the spectrum of low-penetrance common variants. These loci, which can be identified from sufficiently powerful GWASs, together could explain at least 15-20% of the known heritability of these traits. However, for BPC cancers, which have modest familial aggregation, our analysis suggests that risk models based on common variants alone will have modest discriminatory power (63.5% area under curve), even with new discoveries. Twit Text FOAVip Estimation of effect size distribution from genome-wide association studies and implications for future discoveries ????Nat Genet http://www.kidney.de/pget.php?&tw=1&pmid=20562874 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=20562874 #FOAvip English Wikipedia <ref>{{Cite pmid|20562874 }}</ref> Estimation of effect size distribution from genome-wide association studies and implications for future discoveries #MMPMID20562874 Park JH ; Wacholder S ; Gail MH ; Peters U ; Jacobs KB ; Chanock SJ ; Chatterjee N Nat Genet 2010[Jul]; 42 (7 ): 570-5 PMID20562874 show ga We report a set of tools to estimate the number of susceptibility loci and the distribution of their effect sizes for a trait on the basis of discoveries from existing genome-wide association studies (GWASs). We propose statistical power calculations for future GWASs using estimated distributions of effect sizes. Using reported GWAS findings for height, Crohn's disease and breast, prostate and colorectal (BPC) cancers, we determine that each of these traits is likely to harbor additional loci within the spectrum of low-penetrance common variants. These loci, which can be identified from sufficiently powerful GWASs, together could explain at least 15-20% of the known heritability of these traits. However, for BPC cancers, which have modest familial aggregation, our analysis suggests that risk models based on common variants alone will have modest discriminatory power (63.5% area under curve), even with new discoveries. |*Polymorphism, Single Nucleotide [MESH] |Algorithms [MESH] |Body Height/genetics [MESH] |Breast Neoplasms/genetics [MESH] |Colorectal Neoplasms/genetics [MESH] |Crohn Disease/genetics [MESH] |Female [MESH] |Gene Frequency [MESH] |Genetic Predisposition to Disease/*genetics [MESH] |Genome-Wide Association Study/*methods [MESH] |Genotype [MESH] |Humans [MESH] |Male [MESH] |Models, Genetic [MESH] |Penetrance [MESH] |Prostatic Neoplasms/genetics [MESH]Estimation of effect size distribution from genome-wide association st(epmc).pdf DeepDyve Pubget Overpricing