EpiMiner

Detecting and visualizing nonlinear interactive effects of Single Nucleotide Polymorphisms (SNPs) or epistasis are important topics of signal processing and are both mathematical and computational challenges. To address these problems, a multi-stage method, epiMiner, is proposed based on co-information theory. In screening stage, Co-Information Filter (CIF) is employed to visualize and rank contributions of individual SNPs to the phenotype. The number of top ranking SNPs retained to next stage is specified by users directly or a support vector machine classifier automatically. In testing stage, co-information and co-information based permutation test are conducted sequentially to exhaustively search epistasis within the retained SNPs and the final results are then ranked by their p-values. For characterizing broader epistasis landscape, networks are built freely in visualizing stage by linking pairs of the retained SNPs if their co-information values with respect to the phenotype are