In this study, we developed analytical formulae to predict statistical power and to calculate the sample size requirements for detecting the overall QTL effect and for detecting additive and dominance effects separately using flanking markers under the F-2 design. Formulae of statistical power were functions of marker-QTL distance, heritability, type of the QTL effect, sample size, and type-I error and sample size formulae were functions of type-II error and the aforementioned parameters except sample size. Detecting the overall QTL effect had higher statistical power than detecting additive or dominance effect, and detecting additive effect had higher statistical power than detecting dominance effect. The results can be applied to a genome scan by a multiple test correction to the significance level. Compared to single marker analysis, the increase in statistical power due to the use of flanking markers was slight for detecting additive effect but could be substantial for testing additive effect, particularly when the marker-QTL distance is large.
Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume , , 23.19, 2006
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