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Genome-wide association studies (GWAS) are routinely conducted for both quantitative and binary (disease) traits. We present two analytical tools for use in the experimental design of GWAS. Firstly, we present power calculations quantifying power in a unified framework for a range of scenarios. In this context we consider the utility of quantitative scores (e.g. endophenotypes) that may be available on cases only or both cases and controls. Secondly, we consider, the accuracy of prediction of genetic risk from genome-wide SNPs and derive an expression for genomic prediction accuracy using a liability threshold model for disease traits in a case-control design. The expected values based on our derived equations for both power and prediction accuracy agree well with observed estimates from simulations.

Original publication

DOI

10.1371/journal.pone.0071494

Type

Journal

PloS one

Publication Date

01/2013

Volume

8

Addresses

Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia.

Keywords

Humans, Genetic Predisposition to Disease, Case-Control Studies, Genomics, Polymorphism, Single Nucleotide, Genome, Human, Computer Simulation, Genome-Wide Association Study