Basic statistical theory implies that genotypic class cardinalities play a strong role in determining power to detect QTL, but the classes do not contribute equal information to the model. For example, while it is generally accepted that homozygotes contribute more to the detection of additive effects, heterozygotes are necessary to detect dominance effects. The literature on QTL detection often mentions the importance of genotypic class sizes in passing (Belknap (1998); Belknap et al. (1996); Jin et al. (2004); Kliebenstein (2007); Kao (2006); Martinez et al. (2002)), but no rigorous study of their relative values appears to exist. The purpose of this paper is to quantify the relative contribution of the heterozygous class. Researchers can use these results in evaluating the tradeoff between gain in statistical power and the cost of developing populations with specified genotypic class sizes. In addition, we arrive at the surprising conclusion that a misspecified additive model often outperforms a full model that incorporates dominance. This result is significant because standard software packages normally use the full model by default.
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