Figure 1.

Overview of the DeepCOMBI method. Receiving genotypes and phenotypes of a GWAS as input, the DeepCOMBI method first applies a deep learning step to train a DNN for the classification of subjects. Afterward, in the explanation step, it selects the most relevant SNPs by applying LRP to calculate relevance scores for each SNP. Finally, for this set of most relevant SNPs, DeepCOMBI calculates P-values and corresponding significance thresholds in a statistical testing step. This figure is an adjusted version of Figure 1 presented by Mieth et al. (31).