There are multiple tools available to identify, score, and annotate genetic variants within a genome. However, the majority of these tools are restricted to high-penetrance genes for Mendelian diseases and can only analyze certain pedigree structures.

A University of Utah researcher has developed a framework for prioritizing genetic disease variants. This framework, Polymorphism Evaluation, Ranking, and Classification for Heritable traits (PERCH), predicts the pathogenicity of genetic variants better than competing methods. PERCH uses BayesDel, BayesSeg, BayesHLR, and BayesGBA to prioritize variants or gene sets. PERCH measures the biological relevance of each gene to the disease of interest, searching for disease susceptibility genes through whole-exome, whole-genome, or gene-panel sequencing data.