Deogen is a variant-effect predictor that aims at the multi-level contextualization of both the target variant and the affected protein. It performs this contextualization by combining different sources of biological information.
Those sources can be roughly divided into variant-oriented and protein oriented features. The former are evolution-based and aim at predicting the molecular phenotype induced by the variant on the protein, while the latter comprehend information from Protein-protein interaction networks, pathway annotation, degree of recessiveness and essentiality of the gene.
The method has been developed by Daniele Raimondi, Andrea Gazzo, Marianne Rooman, Tom Lenaerts and Wim Vranken and has been published here (doi: 10.1093/bioinformatics/btw094).