Journal of Heredity 2003:94(1)
© 2003 The American Genetic Association 94:1-7
Establishing Appropriate Genome-Wide Significance Levels for Canine Linkage Analyses
From the Laboratory of Statistical Genetics, Rockefeller University, 1230 York Ave., New York, NY, 10021 (Gordon, Corwin, and Ott), and the Divisions of Human Biology and Clinical Research, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N, D4-100, Seattle, WA 98109-1024 (Mellersh and Ostrander). We gratefully acknowledge grants K01-HG00055 (to D.G.), HG00008 (to J.O.), K05 CA90754 (to E.A.O.), and R01 CA92167 (to E.A.O.).
Address correspondence to Derek Gordon, Laboratory of Statistical Genetics, Rockefeller University, Box 192, 1230 York Ave., New York, NY 10021, or e-mail: gordon{at}linkage.rockefeller.edu.
A threshold of 3.3 for a genome-wide maximum LOD score (MAXLOD) has been demonstrated in human linkage studies as corresponding to a type I error rate of 5%. Generalization of this work to other species assumes the presence of an infinitely dense marker map. While this assumption is increasingly realistic for the human genome, it may be unrealistic for the dog genome. In this study we establish the analytic and empirical thresholds for MAXLOD in canine linkage studies corresponding to type I error rates of 5% and 1% for autosomal traits. Empirical thresholds are computed via simulation assuming a 10 cM map with no fine mapping performed. Pedigree structures for simulations were drawn from two canine disease studies. Five thousand replicates of genome-wide null genotype data were simulated and analyzed for each disease. We determined that MAXLOD thresholds of 3.2 and 2.7 correspond to analytic and empirical type I error rates of 5%, respectively. In all cases, the MAXLOD thresholds from simulations were always at least 0.5 LOD units below the corresponding analytic thresholds. We therefore recommend that a threshold of 3.2 be used for canine linkage studies when fine mapping is performed, and that researchers perform their own simulation studies to assess genome-wide empirical significance levels when no fine mapping is performed.