ArticleNPJ genomic medicine2018
A phenotype centric benchmark of variant prioritisation tools.
Article in NPJ genomic medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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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
24 citing papers in PubMed, 46 citations in OpenAlex.
- Predicting the Damaging Potential of UncharacterizedInternational journal of molecular sciences · 2025Article
- An augmented transformer model trained on protein family specific variant data leads to improved prediction of variants of uncertain significance.Human genetics · 2025Article
- A Novel Missense Variant in SORBS2 Is Causative With Familial Alzheimer's Disease.CNS neuroscience & therapeutics · 2025Article
- Identification and in-silico characterization of splice-site variants from a large cardiogenetic national registry.European journal of human genetics : EJHG · 2023Article
- Article
- Utility of tissue-specific gene expression scores for gene prioritization in Mendelian diseases.Journal of human genetics · 2022Article
- An expanded phenotype centric benchmark of variant prioritisation tools.Human mutation · 2022Article
- Interpreting the spectrum of gamma-secretase complex missense variation in the context of hidradenitis suppurativa-AnFrontiers in genetics · 2022Article
- Clinical significance of genetic variation in hypertrophic cardiomyopathy: comparison of computational tools to prioritize missense variants.Frontiers in cardiovascular medicine · 2022Article
- An overview of germline variations in genes of primary immunodeficiences through integrative analysis of ClinVar, HGMDHuman genetics · 2021Article
- L-Type Calcium Channel: Predicting Pathogenic/Likely Pathogenic Status for Variants of Uncertain Clinical Significance.Membranes · 2021Article
- Article
- A flexible computational pipeline for research analyses of unsolved clinical exome cases.NPJ genomic medicine · 2020Article
- Problems in variation interpretation guidelines and in their implementation in computational tools.Molecular genetics & genomic medicine · 2020Article
- Family-specific analysis of variant pathogenicity prediction tools.NAR genomics and bioinformatics · 2020Article
- Variant effect predictions capture some aspects of deep mutational scanning experiments.BMC bioinformatics · 2020Article
- Matching whole genomes to rare genetic disorders: Identification of potential causative variants using phenotype-weighted knowledge in the CAGI SickKids5 clinical genomes challenge.Human mutation · 2020Article
- Variation benchmark datasets: update, criteria, quality and applications.Database : the journal of biological databases and curation · 2020Article
- Personalised analytics for rare disease diagnostics.Nature communications · 2019Article
- Genetic regulatory variation in populations informs transcriptome analysis in rare disease.Science (New York, N.Y.) · 2019Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Next generation sequencing is a standard tool used in clinical diagnostics. In Mendelian diseases the challenge is to discover the single etiological variant among thousands of benign or functionally unrelated variants. After calling variants from aligned sequencing reads, variant prioritisation tools are used to examine the conservation or potential functional consequences of variants. We hypothesised that the performance of variant prioritisation tools may vary by disease phenotype. To test this we created benchmark data sets for variants associated with different disease phenotypes. We found that performance of 24 tested tools is highly variable and differs by disease phenotype. The task of identifying a causative variant amongst a large number of benign variants is challenging for all tools, highlighting the need for further development in the field. Based on our observations, we recommend use of five top performers found in this study (FATHMM, M-CAP, MetaLR, MetaSVM and VEST3). In addition we provide tables indicating which analytical approach works best in which disease context. Variant prioritisation tools are best suited to investigate variants associated with well-studied genetic diseases, as these variants are more readily available during algorithm development than variants associated with rare diseases. We anticipate that further development into disease focussed tools will lead to significant improvements.
Identifiers
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.