ArticleGenetics in medicine : official journal of the American College of Medical Genetics2022
Evaluating the impact of in silico predictors on clinical variant classification.
Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed, 56 citations in OpenAlex.
- HBOCpred: An Ensemble Framework for Prioritisation of Germline Missense Variants in Hereditary Breast and Ovarian Cancer.International journal of molecular sciences · 2026Article
- The population frequency of predicted pathogenic genetic variants in commonly affected CAKUT genes in the general population.Pediatric nephrology (Berlin, Germany) · 2026Article
- Article
- A prioritization framework for BRCA1/2 variants of uncertain significance identified by comprehensive genomic profiling.European journal of human genetics : EJHG · 2026Article
- RNA Sequencing Resolves Cryptic Pathogenic Variants in Mitochondrial Disease.Annals of clinical and translational neurology · 2026Article
- Reclassification of missense variant pathogenicity using ClinGen recommendations for recalibrated PP3/BP4 in silico predictor score thresholds.Genetics in medicine open · 2026Article
- The Performance ofHuman mutation · 2026Article
- Case Report: A novel variant in fibrillin-2 identified in a congenital contractural arachnodactyly family with phenotypic heterogeneity.Frontiers in medicine · 2026Article
- Enhancing missense variant classification in predicted intrinsically disordered regions.PloS one · 2026Article
- MutAnt: mutation annotation tool predicts deleteriousness of missense mutations and improves mutation calling from transcriptomics.Human genetics · 2025Article
- Functional characterization of alleLife · 2025Article
- Frequency of Mutations in theMedicina (Kaunas, Lithuania) · 2024Article
- Regional-specific calibration enables application of computational evidence for clinical classification of 5' cis-regulatory variants in Mendelian disease.American journal of human genetics · 2024Article
- Explicable prioritization of genetic variants by integration of rule-based and machine learning algorithms for diagnosis of rare Mendelian disorders.Human genomics · 2024Article
- Next-generation sequencing and bioinformatics in rare movement disorders.Nature reviews. Neurology · 2024Review
- Characterizing the pathogenicity of genetic variants: the consequences of context.NPJ genomic medicine · 2024Article
- MAGPIE: accurate pathogenic prediction for multiple variant types using machine learning approach.Genome medicine · 2024Article
- Comprehensive evaluation of AlphaMissense predictions by evidence quantification for variants of uncertain significance.Frontiers in genetics · 2024Article
- Compilation of Genotype and Phenotype Data inGenes · 2023Article
- Finding significance: New perspectives in variant classification of the RAD51 regulators, BRCA2 and beyond.DNA repair · 2023Review
Corrections and comments
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Authors and funding
7 authors at 5 institutions in 2 countries.
Funding
Abstract
purposeAccording to the American College of Medical Genetics and Genomics/Association of Medical Pathology (ACMG/AMP) guidelines, in silico evidence is applied at the supporting strength level for pathogenic (PP3) and benign (BP4) evidence. Although PP3 is commonly used, less is known about the effect of these criteria on variant classification outcomes.
methodsA total of 727 missense variants curated by Clinical Genome Resource expert groups were analyzed to determine how often PP3 and BP4 were applied and their impact on variant classification. The ACMG/AMP categorical system of variant classification was compared with a quantitative point-based system. The pathogenicity likelihood ratios of REVEL, VEST, FATHMM, and MPC were calibrated using a gold standard set of 237 pathogenic and benign variants (classified independent of the PP3/BP4 criteria).
resultsThe PP3 and BP4 criteria were applied by Variant Curation Expert Panels to 55% of missense variants. Application of those criteria changed the classification of 15% of missense variants for which either criterion was applied. The point-based system resolved borderline classifications. REVEL and VEST performed best at a strength level consistent with moderate evidence.
conclusionWe show that in silico criteria are commonly applied and often affect the final variant classifications. When appropriate thresholds for in silico predictors are established, our results show that PP3 and BP4 can be used at a moderate strength.
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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.