Table 1

Summary of the objectives and design of simulations 1-3
Simulation 1 Simulation 2 Simulation 3
Objective To compare RF VIMs for main and interaction effect detection. To compare RF measures with p-values from logistic regression for main and interaction effect detection. Examine RF performance in presence of realistic patterns of LD and MAF.
Independent SNPs Yes Yes No (LD)
# Total Loci (p) 10, 100, 500, 1000 10, 100, 500, 1000 Fixed at 1000
# Causal Loci (k) 4 2 2
MAF Fixed at 0.1, 0.2, 0.3, or 0.4 Fixed at 0.3 Varies (0.01–0.50)
# Model Scenarios 5 3 4
Description Varying effect sizes, HX1X22 vs. HX3X42 Two interacting SNPs with 0, 1, or 2 having main effects. Causal SNPs chosen in blocks of strong vs. weak LD with non-causal SNPs.
Phenotype Generation Phenotype is a dichotomized quantitative (normally distributed) trait. Phenotype is based on direct penetrance functions. Phenotypes are generated as in Simulation 1.

Winham et al.

Winham et al. BMC Bioinformatics 2012 13:164   doi:10.1186/1471-2105-13-164

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