PERCH: A Unified Framework for Disease Gene Prioritization: HUMAN MUTATION
Open accessAbstract
To interpret genetic variants discovered from next-generation sequencing, integration of heterogeneous information is vital for success. This article describes a framework named PERCH (Polymorphism Evaluation, Ranking, and Classification for a Heritable trait), available at http://BJFengLab.org/. It can prioritize disease genes by quantitatively unifying a new deleteriousness measure called BayesDel, an improved assessment of the biological relevance of genes to the disease, a modified linkage analysis, a novel rare-variant association test, and a converted variant call quality score. It supports data that contain various combinations of extended pedigrees, trios, and case-controls, and allows for a reduced penetrance, an elevated phenocopy rate, liability classes, and covariates. BayesDel is more accurate than PolyPhen2, SIFT, FATHMM, LRT, Mutation Taster, Mutation Assessor, PhyloP, GERP++, SiPhy, CADD, MetaLR, and MetaSVM. The overall approach is faster and more powerful than the existing quantitative method pVAAST, as shown by the simulations of challenging situations in finding the missing heritability of a complex disease. This framework can also classify variants of unknown significance (variants of uncertain significance) by quantitatively integrating allele frequencies, deleteriousness, association, and co-segregation. PERCH is a versatile tool for gene prioritization in gene discovery research and variant classification in clinical genetic testing.
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- Authors
- Feng, B.-J.
- Affiliations
- University of Utah (US)
- Corresponding author
- Feng, Bing-Jian
- ORCID
- Feng, Bing-Jian
- Venue
- Human Mutation
- Publisher
- Wiley
- Published
- 2017-01-28
- Volume
- 38
- Issue
- 3
- Pages
- 243-251
- ISSN
- 1059-7794 (ISSN-L)
- PMC
- PMC5299048
- OpenAlex
- W2561724945
- Cited by
- 289
- References
- 56
- Citations by year
- 2026: 57 · 2025: 73 · 2024: 51 · 2023: 35 · 2022: 32 · 2021: 18 · 2020: 13 · 2019: 5 · 2018: 3 · 2017: 1
- FWCI
- 2.42
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Human Mutation (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (CA116167, CA192393, CA155767, CA164944)
- National Psoriasis Foundation
- Utah Genome Project
- PERSPECTIVE (PErsonalised Risk Stratification for Prevention and Early deteCTIon of breast cancer) Project
- National Cancer Institute (CA116167, CA164138, CA192393)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- disease gene prioritization, perch, linkage analysis, variant interpretation, variants of uncertain significance, missing heritability, complex diseases, phenocopy, incomplete penetrance, pedigree analysis, trios, case-control, allele frequency, co-segregation, clinical genetic testing
- MeSH terms
- Humans, ROC Curve, Software, Reproducibility of Results, Computational Biology, Quantitative Trait, Heritable, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Genetic Association Studies
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