Perch: Enhanced Genetic Variant Prioritization

ID U-6647

Category Digital Health

Subcategory Bioinformatics

Researchers
Brief Summary

Software that integrates Bayesian analyses for enhanced prediction of genetic variants’ pathogenicity.

Problem Statement

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.

Technology Description

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.

Stage of Development

Application Design

Benefit

  • Provides a more accurate disease variant pathogenicity score than competing tools.
  • Can be used for disease gene discovery research and new rare variant association.
  • Can be implemented in IARC guidelines or can be integrated into ACMG guidelines.
  • Automates analysis by calculating every possible variant in the human exome.
  • Enables a variety of study designs including case-control samples, extended pedigrees, nuclear pedigrees, or admixtures of the above.

Publications

Feng, B. (2017). PERCH: A Unified Framework for Disease Gene Prioritization. Human Mutation, 38(3), 243-251. doi: 10.1002/humu.23158

Contact Info

Jonathan Tyler
801-587-0515
jonathan.tyler@utah.edu

Questions?

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