ArticleGenetics in medicine : official journal of the American College of Medical Genetics2016
Computational evaluation of exome sequence data using human and model organism phenotypes improves diagnostic efficiency.
Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.
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Who cites it
65 citing papers in PubMed.
- Incremental yield of genome sequencing after exome sequencing for nonimmune hydrops fetalis spectrum.American journal of obstetrics & gynecology MFM · 2026Article
- The Importance of Clinical Acumen for Prenatal Diagnosis in an Increasingly Technological World.Prenatal diagnosis · 2026Article
- Phenotype-first patient matching with SimPheny identifies diagnostic candidates beyond curated gene associations.medRxiv : the preprint server for health sciences · 2026Article
- Accelerate the discovery of genetic variants in mitochondrial diseases with Variant prIOritization using Latent spAce.Briefings in bioinformatics · 2025Article
- An optimized variant prioritization process for rare disease diagnostics: recommendations for Exomiser and Genomiser.Genome medicine · 2025Article
- Clinical and data-driven optimization of Genomiser for rare disease patients: experience from the Hong Kong Genome Project.Briefings in bioinformatics · 2025Article
- Improving automated deep phenotyping through large language models using retrieval-augmented generation.Genome medicine · 2025Article
- Identification of technically challenging variants: Whole-genome sequencing improves diagnostic yield in patients with high clinical suspicion of rare diseases.HGG advances · 2025Article
- Towards a standard benchmark for phenotype-driven variant and gene prioritisation algorithms: PhEval - Phenotypic inference Evaluation framework.BMC bioinformatics · 2025Article
- An AI-based approach driven by genotypes and phenotypes to uplift the diagnostic yield of genetic diseases.Human genetics · 2025Article
- Article
- Efficient reinterpretation of rare disease cases using Exomiser.NPJ genomic medicine · 2024Article
- A Copernican revolution of multigenic analysis: A retrospective study on clinical exome sequencing in unclear genetic disorders.Computational and structural biotechnology journal · 2024Article
- 7p22.3 microdeletion: a case study of a patient with congenital heart defect, neurodevelopmental delay and epilepsy.Orphanet journal of rare diseases · 2024Article
- Exome and genome sequencing in a heterogeneous population of patients with rare disease: Identifying predictors of a diagnosis.Genetics in medicine : official journal of the American College of Medical Genetics · 2024Article
- Critical assessment of variant prioritization methods for rare disease diagnosis within the rare genomes project.Human genomics · 2024Article
- Improving prenatal diagnosis through standards and aggregation.Prenatal diagnosis · 2024Review
- SSLpheno: a self-supervised learning approach for gene-phenotype association prediction using protein-protein interactions and gene ontology data.Bioinformatics (Oxford, England) · 2023Article
- Critical assessment of variant prioritization methods for rare disease diagnosis within the Rare Genomes Project.medRxiv : the preprint server for health sciences · 2023Article
- IMPROVE-DD: Integrating multiple phenotype resources optimizes variant evaluation in genetically determined developmental disorders.HGG advances · 2023Article
5 more citing papers are in PubMed but not listed here.
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Authors and funding
33 authors.
Funding
Abstract
purposeMedical diagnosis and molecular or biochemical confirmation typically rely on the knowledge of the clinician. Although this is very difficult in extremely rare diseases, we hypothesized that the recording of patient phenotypes in Human Phenotype Ontology (HPO) terms and computationally ranking putative disease-associated sequence variants improves diagnosis, particularly for patients with atypical clinical profiles.
methodsUsing simulated exomes and the National Institutes of Health Undiagnosed Diseases Program (UDP) patient cohort and associated exome sequence, we tested our hypothesis using Exomiser. Exomiser ranks candidate variants based on patient phenotype similarity to (i) known disease-gene phenotypes, (ii) model organism phenotypes of candidate orthologs, and (iii) phenotypes of protein-protein association neighbors.
resultsBenchmarking showed Exomiser ranked the causal variant as the top hit in 97% of known disease-gene associations and ranked the correct seeded variant in up to 87% when detectable disease-gene associations were unavailable. Using UDP data, Exomiser ranked the causative variant(s) within the top 10 variants for 11 previously diagnosed variants and achieved a diagnosis for 4 of 23 cases undiagnosed by clinical evaluation.
conclusionStructured phenotyping of patients and computational analysis are effective adjuncts for diagnosing patients with genetic disorders.Genet Med 18 6, 608-617.
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