Application of Multi-SNP Approaches Bayesian LASSO and AUC-RF to Detect Main Effects of Inflammatory-Gene Variants Associated with Bladder Cancer Risk
Figure 2
Venn diagrams showing the overlapping between the SNPs selected by Bayesian Threshold model (BTL) and AUC-Random Forest (AUC-RF).
(A) Number of SNPs detected by each method in the total population. (B) Number of SNPs detected by each method in the non-smoker subset. (C) Number of common SNPs detected by BTL in the total population and non-smoker subset, with posterior probabilities of at least 80% and 75% of having an effect different from 0. (D) Number of SNPs detected by AUC-RF in both the total population and the non-smoker subset.