GWAPower: a statistical power calculation software for genome-wide association studies with quantitative traits

• Main Authors: Chen Chia-Cheng, Wang Shengchu, Feng Sheng, Lan Lan
• Format: Article
• Language: English
• Published: BMC 2011-01-01
• Series: BMC Genetics
• Online Access: http://www.biomedcentral.com/1471-2156/12/12

<p>Abstract</p> <p>Background</p> <p>In designing genome-wide association (GWA) studies it is important to calculate statistical power. General statistical power calculation procedures for quantitative measures often require information concerning summary statistics of distributions such as mean and variance. However, with genetic studies, the effect size of quantitative traits is traditionally expressed as heritability, a quantity defined as the amount of phenotypic variation in the population that can be ascribed to the genetic variants among individuals. Heritability is hard to transform into summary statistics. Therefore, general power calculation procedures cannot be used directly in GWA studies. The development of appropriate statistical methods and a user-friendly software package to address this problem would be welcomed.</p> <p>Results</p> <p>This paper presents GWAPower, a statistical software package of power calculation designed for GWA studies with quantitative traits, where genetic effect is defined as heritability. Based on several popular one-degree-of-freedom genetic models, this method avoids the need to specify the non-centrality parameter of the F-distribution under the alternative hypothesis. Therefore, it can use heritability information directly without approximation. In GWAPower, the power calculation can be easily adjusted for adding covariates and linkage disequilibrium information. An example is provided to illustrate GWAPower, followed by discussions.</p> <p>Conclusions</p> <p>GWAPower is a user-friendly free software package for calculating statistical power based on heritability in GWA studies with quantitative traits. The software is freely available at: <url>http://dl.dropbox.com/u/10502931/GWAPower.zip</url></p>