## Abstract An appealing genome‐wide association study design compares one large control group against several disease samples. A pioneering study by the Wellcome Trust Case Control Consortium that employed such a design has identified multiple susceptibility regions, many of which have been indepe
Bayes factors for genome-wide association studies: comparison with P-values
✍ Scribed by Jon Wakefield
- Publisher
- John Wiley and Sons
- Year
- 2009
- Tongue
- English
- Weight
- 172 KB
- Volume
- 33
- Category
- Article
- ISSN
- 0741-0395
No coin nor oath required. For personal study only.
✦ Synopsis
Abstract
The Bayes factor is a summary measure that provides an alternative to the P‐value for the ranking of associations, or the flagging of associations as “significant”. We describe an approximate Bayes factor that is straightforward to use and is appropriate when sample sizes are large. We consider various choices of the prior on the effect size, including those that allow effect size to vary with the minor allele frequency (MAF) of the marker. An important contribution is the description of a specific prior that gives identical rankings between Bayes factors and P‐values, providing a link between the two approaches, and allowing the implications of the use of P‐values to be more easily understood. As a summary measure of noteworthiness P‐values are difficult to calibrate since their interpretation depends on MAF and, crucially, on sample size. A consequence is that a consistent decision‐making procedure using P‐values requires a threshold for significance that reduces with sample size, contrary to common practice. Genet. Epidemiol. 2008. © 2008 Wiley‐Liss, Inc.
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