ReviewTrends in genetics : TIG2022
Phenotype-aware prioritisation of rare Mendelian disease variants.
Review in Trends in genetics : TIG, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
26 citing papers in PubMed, 33 citations in OpenAlex.
- PhenoSS: phenotype semantic similarity-based approach for rare disease prediction and patient clustering.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Global recommendations for the use of diagnostic genomic sequencing in the prenatal setting on behalf of the ESHG and ISPD.European journal of human genetics : EJHG · 2026Article
- Whole genome sequencing in cerebral palsy: a UK paediatric pilot study.The Lancet regional health. Europe · 2026Article
- A global survey of systems biology-based predictions of gene-rare disease associations to enhance new diagnoses.Scientific reports · 2026Article
- PhenoSS: Phenotype semantic similarity-based approach for rare disease prediction and patient clustering.medRxiv : the preprint server for health sciences · 2026Article
- Comprehensive evaluation of ACMG/AMP-based variant classification tools.Bioinformatics (Oxford, England) · 2026Article
- Benchmarking knowledge graph embedding models for the prediction of oligogenic combinations.Briefings in bioinformatics · 2026Article
- Single vs dual genetic disease in children with congenital anomalies and solid tumors.Genetics in medicine open · 2026Article
- Accelerate the discovery of genetic variants in mitochondrial diseases with Variant prIOritization using Latent spAce.Briefings in bioinformatics · 2025Article
- Performance of ChatGPT-4o and Four Open-Source Large Language Models in Generating Diagnoses Based on China's Rare Disease Catalog: Comparative Study.Journal of medical Internet research · 2025Article
- Enhancing the Accuracy of Human Phenotype Ontology Identification: Comparative Evaluation of Multimodal Large Language Models.Journal of medical Internet research · 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
- Evaluating seven bioinformatics platforms for tertiary analysis of genomic data from whole exome sequencing in a pilot group of patients.Advances in laboratory medicine · 2025Article
- Leveraging clinical intuition to improve accuracy of phenotype-driven prioritization.Genetics in medicine : official journal of the American College of Medical Genetics · 2025Article
- Next-generation phenotyping of inherited retinal diseases from multimodal imaging with Eye2Gene.Nature machine intelligence · 2025Article
- Differential expression and co-expression reveal cell types relevant to genetic disorder phenotypes.Bioinformatics (Oxford, England) · 2024Article
- Article
- Improving prenatal diagnosis through standards and aggregation.Prenatal diagnosis · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
Abstract
A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices.
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What OpenQuestion holds
Registered trials
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.