Format

Send to

Choose Destination
See comment in PubMed Commons below
AMIA Annu Symp Proc. 2011;2011:617-24. Epub 2011 Oct 22.

Evaluating de novo locus-disease discoveries in GWAS using the signal-to-noise ratio.

Author information

  • 1Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA.

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.

PMID:
22195117
PMCID:
PMC3243170
[PubMed - indexed for MEDLINE]
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for PubMed Central
    Loading ...
    Support Center