ArticleBioinformatics (Oxford, England)2015
OVA: integrating molecular and physical phenotype data from multiple biomedical domain ontologies with variant filtering for enhanced variant prioritization.
Article in Bioinformatics (Oxford, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Phenotype-aware prioritisation of rare Mendelian disease variants.Trends in genetics : TIG · 2022Review
- Copy number variant analysis for syndromic congenital heart disease in the Chinese population.Human genomics · 2022Article
- Phenotype-driven approaches to enhance variant prioritization and diagnosis of rare disease.Human mutation · 2022Review
- Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases.Briefings in bioinformatics · 2022Article
- GeneTerpret: a customizable multilayer approach to genomic variant prioritization and interpretation.BMC medical genomics · 2022Article
- A pipeline-friendly software tool for genome diagnostics to prioritize genes by matching patient symptoms to literature.Advanced genetics (Hoboken, N.J.) · 2020Article
- VarFish: comprehensive DNA variant analysis for diagnostics and research.Nucleic acids research · 2020Article
- Phen2Gene: rapid phenotype-driven gene prioritization for rare diseases.NAR genomics and bioinformatics · 2020Article
- Article
- Using mechanistic models for the clinical interpretation of complex genomic variation.Scientific reports · 2019Article
- MutationDistiller: user-driven identification of pathogenic DNA variants.Nucleic acids research · 2019Article
- Phenotype-driven gene prioritization for rare diseases using graph convolution on heterogeneous networks.BMC medical genomics · 2018Article
- Evaluating phenotype-driven approaches for genetic diagnoses from exomes in a clinical setting.Scientific reports · 2017Article
- QueryOR: a comprehensive web platform for genetic variant analysis and prioritization.BMC bioinformatics · 2017Article
- PCAN: phenotype consensus analysis to support disease-gene association.BMC bioinformatics · 2016Article
- Challenges of Identifying Clinically Actionable Genetic Variants for Precision Medicine.Journal of healthcare engineering · 2016Review
- Advances in understanding - genetic basis of intellectual disability.F1000Research · 2016Review
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Authors and funding
8 authors.
Funding
Abstract
motivationExome sequencing has become a de facto standard method for Mendelian disease gene discovery in recent years, yet identifying disease-causing mutations among thousands of candidate variants remains a non-trivial task.
resultsHere we describe a new variant prioritization tool, OVA (ontology variant analysis), in which user-provided phenotypic information is exploited to infer deeper biological context. OVA combines a knowledge-based approach with a variant-filtering framework. It reduces the number of candidate variants by considering genotype and predicted effect on protein sequence, and scores the remainder on biological relevance to the query phenotype.We take advantage of several ontologies in order to bridge knowledge across multiple biomedical domains and facilitate computational analysis of annotations pertaining to genes, diseases, phenotypes, tissues and pathways. In this way, OVA combines information regarding molecular and physical phenotypes and integrates both human and model organism data to effectively prioritize variants. By assessing performance on both known and novel disease mutations, we show that OVA performs biologically meaningful candidate variant prioritization and can be more accurate than another recently published candidate variant prioritization tool. AVAILABILITY AND IMPLEMENTATION: OVA is freely accessible at http://dna2.leeds.ac.uk:8080/OVA/index.jsp. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. CONTACT: umaan@leeds.ac.uk.
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