ArticleBMC medical genomics2014
PhenoVar: a phenotype-driven approach in clinical genomics for the diagnosis of polymalformative syndromes.
Article in BMC medical genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 30 citations in OpenAlex.
- Multimodal integrated knowledge transfer to large language models through preference optimization with biomedical applications.Patterns (New York, N.Y.) · 2026Article
- A Hypergraph powered approach to Phenotype-driven Gene Prioritization and Rare Disease Prediction.Scientific reports · 2025Article
- High-throughput Second-generation Sequencing Technology Assisted Diagnosis of Familial Partial Lipodystrophy (Type 2 Kobberling-Dunnigan Syndrome): A Case Report.Combinatorial chemistry & high throughput screening · 2024Article
- Individualised human phenotype ontology gene panels improve clinical whole exome and genome sequencing analytical efficacy in a cohort of developmental and epileptic encephalopathies.Molecular genetics & genomic medicine · 2023Article
- Phenotype-aware prioritisation of rare Mendelian disease variants.Trends in genetics : TIG · 2022Review
- Diagnostic yield and clinical utility of whole exome sequencing using an automated variant prioritization system, EVIDENCE.Clinical genetics · 2020Article
- Article
- Mutation update for the SATB2 gene.Human mutation · 2019Review
- ClinPhen extracts and prioritizes patient phenotypes directly from medical records to expedite genetic disease diagnosis.Genetics in medicine : official journal of the American College of Medical Genetics · 2019Article
- Novel phenotype-disease matching tool for rare genetic diseases.Genetics in medicine : official journal of the American College of Medical Genetics · 2019Article
- Clinical validity of phenotype-driven analysis software PhenoVar as a diagnostic aid for clinical geneticists in the interpretation of whole-exome sequencing data.Genetics in medicine : official journal of the American College of Medical Genetics · 2018Article
- A new method to measure the semantic similarity from query phenotypic abnormalities to diseases based on the human phenotype ontology.BMC bioinformatics · 2018Article
- The functional genomics laboratory: functional validation of genetic variants.Journal of inherited metabolic disease · 2018Review
- The Human Phenotype Ontology in 2017.Nucleic acids research · 2017Review
- Computational evaluation of exome sequence data using human and model organism phenotypes improves diagnostic efficiency.Genetics in medicine : official journal of the American College of Medical Genetics · 2016Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWe propose a phenotype-driven analysis of encrypted exome data to facilitate the widespread implementation of exome sequencing as a clinical genetic screening test.Twenty test-patients with varied syndromes were selected from the literature. For each patient, the mutation, phenotypic data, and genetic diagnosis were available. Next, control exome-files, each modified to include one of these twenty mutations, were assigned to the corresponding test-patients. These data were used by a geneticist blinded to the diagnoses to test the efficiency of our software, PhenoVar. The score assigned by PhenoVar to any genetic diagnosis listed in OMIM (Online Mendelian Inheritance in Man) took into consideration both the patient's phenotype and all variations present in the corresponding exome. The physician did not have access to the individual mutations. PhenoVar filtered the search using a cut-off phenotypic match threshold to prevent undesired discovery of incidental findings and ranked the OMIM entries according to diagnostic score.
resultsWhen assigning the same weight to all variants in the exome, PhenoVar predicted the correct diagnosis in 10/20 patients, while in 15/20 the correct diagnosis was among the 4 highest ranked diagnoses. When assigning a higher weight to variants known, or bioinformatically predicted, to cause disease, PhenoVar's yield increased to 14/20 (18/20 in top 4). No incidental findings were identified using our cut-off phenotypic threshold.
conclusionThe phenotype-driven approach described could render widespread use of ES more practical, ethical and clinically useful. The implications about novel disease identification, advancement of complex diseases and personalized medicine are discussed.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.