ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2011
Evaluating de novo locus-disease discoveries in GWAS using the signal-to-noise ratio.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
A genome-wide association study (GWAS) involves examining representative SNPs obtained using high throughput technologies. A GWAS data set can entail a million SNPs and may soon entail many millions. In a GWAS researchers often investigate the correlation of each SNP with a disease. With so many hypotheses, it is not straightforward how to interpret the results. Strategies include using the Bonferroni correction to determine the significance of a model and Bayesian methods. However, when we are discovering new locus-disease associations, i.e., so called de novo discoveries, we should not just endeavor to determine the significance of particular models, but also concern ourselves with determining whether it is likely that we have any true discoveries, and if so how many of the highest ranking models we should investigate further. We develop a method based on a signal-to-noise ratio that targets this issue. We apply the method to a GWAS Alzheimer's data set.
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22195117PMC3243170What OpenQuestion holds
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