Designing a GWAS: power, sample size, and data structure.

@article{Ball2013DesigningAG,
  title={Designing a GWAS: power, sample size, and data structure.},
  author={Roderick D. Ball},
  journal={Methods in molecular biology},
  year={2013},
  volume={1019},
  pages={37-98}
}
In this chapter we describe a novel Bayesian approach to designing GWAS studies with the goal of ensuring robust detection of effects of genomic loci associated with trait variation.The goal of GWAS is to detect loci associated with variation in traits of interest. Finding which of 500,000-1,000,000 loci has a practically significant effect is a difficult statistical problem, like finding a needle in a haystack. We address this problem by designing experiments to detect effects with a given… CONTINUE READING