European Journal of Environment and Public Health · 2018 · 17 citations · 13 references
Life SciencesBiostatisticsGeneticsGenomicsQuantitative GeneticsStatistical GeneticsComplex Trait GeneticsGenome-wide Association StudiesGenotype-phenotype Association AnalysisGenotype-phenotype CorrelationQuantitative Trait AnalysisAlternative HypothesisAlternative Hypothesis FormulationGenetic Effect Size DistributionGenome-wide Association MappingQuantitative Trait GeneticsStatistical Power AnalysisStatistical Power In Association StudiesTest Frequencies
A power calculation for a study with a quantitative outcome requires information on the outcome distribution under the alternative hypothesis. Researchers face challenges when they concisely specify alternative distributions in genetic studies because power depends on genotype frequencies and the average effect of each genotype. In GWAS, investigators evaluate hundreds of thousands of associations; therefore it is unrealistic to specify gene frequencies and gene effects for each test and some simplification is needed. Software packages are available to calculate power, but many of them have limited flexibility and / or may have a steep learning curve. In this review, we describe to researchers and graduate students the essentials of a power calculation for testing for an association between a quantitative trait and genotypes. In addition, we provide them with the codes of the different available software packages-free and commercial-to calculate this power. The calculations can be carried out using virtually any computer language that computes the cumulative distribution function of a non-central F-distribution.
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Continuous Univariate Distributions.
Yasuhiro Omori, Norman L. Johnson, S. Kotz et al. · Journal of the American Statistical Association · 1995 · 9.3K citations
Power and sample size calculations
William D. Dupont, W. Dale Plummer · Controlled Clinical Trials · 1990 · 2.1K citations