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Table 2 Number of SNPs in simulation study 1 with empirical power > 0

From: r2VIM: A new variable selection method for random forests in genome-wide association studies

Method n mtry Factor Total Causal High LD Mod LD Low LD FP
LR 2000    40 8 15 11 4 0
LR 6000    98 9 16 15 15 0
r2VIM 2000 100000 1 38 7 13 10 2 4
r2VIM 2000 100000 3 28 7 12 6 2 0
r2VIM 2000 100000 5 24 7 10 5 2 0
r2VIM 2000 250000 1 40 8 12 9 2 8
r2VIM 2000 250000 3 25 7 9 5 2 1
r2VIM 2000 250000 5 23 7 9 5 2 0
r2VIM 6000 100000 1 51 9 16 10 5 3
r2VIM 6000 100000 3 41 9 16 6 4 0
r2VIM 6000 100000 5 37 9 16 6 4 0
r2VIM 6000 250000 1 63 9 16 12 6 13
r2VIM 6000 250000 3 42 9 16 7 4 1
r2VIM 6000 250000 5 37 9 16 5 4 0
  1. Shown are results for logistic regression (LR) and r2VIM. Columns denote method, sample size (n), mtry parameter and factor for r2VIM, total number of SNPs, number of SNPs in strong (r 2 > 0.8), moderate LD (0.5 < r 2 ≤ 0.8) and low LD (0.3 < r 2 ≤ 0.5) with any causal SNP as well as number of false-positive SNPs (FP)