Power analysis for genome-wide association studies
نویسندگان
چکیده
منابع مشابه
Prioritized subset analysis: improving power in genome-wide association studies.
BACKGROUND Genome-wide association studies (GWAS) are now feasible for studying the genetics underlying complex diseases. For many diseases, a list of candidate genes or regions exists and incorporation of such information into data analyses can potentially improve the power to detect disease variants. Traditional approaches for assessing the overall statistical significance of GWAS results ign...
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Individual genome-wide association studies have only limited power to find novel loci underlying complex traits and common diseases. With relatively modest sample and effect sizes, a true association between genotype and phenotype may never meet genome-wide statistical significance (P < 5 x 10(-8)) in a single study. Through meta-analysis, novel susceptibility loci can be discovered by effectiv...
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Progress in probabilistic generative models has accelerated, developing richer models with neural architectures, implicit densities, and with scalable algorithms for their Bayesian inference. However, there has been limited progress in models that capture causal relationships, for example, how individual genetic factors cause major human diseases. In this work, we focus on two challenges in par...
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ژورنال
عنوان ژورنال: BMC Genetics
سال: 2007
ISSN: 1471-2156
DOI: 10.1186/1471-2156-8-58