An extensive comparison of quantitative trait Loci mapping methods.

BACKGROUND

The choices of study design and statistical approach for mapping a quantitative trait (QT) are of great importance. Larger sibships and a study design based upon phenotypically extreme siblings can be expected to have a greater statistical power. On the other hand, selected samples and/or deviation from normality can influence the robustness and power. Unfortunately, the effects of violation of multivariate normality assumptions and/or selected samples are only known for a limited number of methods. Some recommendations are available in the literature, but an extensive comparison of robustness and power under several different conditions is lacking.

METHODS

We compared eight freely available and commonly applied QT mapping methods in a Monte-Carlo simulation study under 36 different models and study designs (three genetic models, three selection schemes, two family structures and the possible effect of deviation from normality).

RESULTS

Empirical type I error fractions and empirical power are presented and explained as a whole and for each method separately, followed by a thorough discussion.

CONCLUSIONS

The results from this extensive comparison could serve as a valuable source for the choice of the study design and the statistical approach for mapping a QT.