Supplementary Material for: An Extensive Comparison of Quantitative Trait Loci Mapping Methods Kleensang A. Franke D. Alcaïs A. Abel L. Müller-Myhsok B. Ziegler A. 10.6084/m9.figshare.5121064.v1 https://karger.figshare.com/articles/dataset/Supplementary_Material_for_An_Extensive_Comparison_of_Quantitative_Trait_Loci_Mapping_Methods/5121064 <i>Background:</i> 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. <i>Methods:</i> 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). <i>Results:</i> 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. <i>Conclusions:</i> 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. 2010-03-05 00:00:00 QTL Monte-Carlo simulation study Linkage Type I error Empirical power