ArticleAmerican journal of human genetics2024
Calibration of variant effect predictors on genome-wide data masks heterogeneous performance across genes.
Article in American journal of human genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Applications of artificial intelligence in early childhood health management: a systematic review from fetal to pediatric periods.Frontiers in pediatrics · 2025Pooled it
- An integrated, scaled approach to resolve TSC2 variants of uncertain significance.Nature communications · 2026Article
- Phenotype-Specific Recalibration of MAVE Data Enables Repurposing ofmedRxiv : the preprint server for health sciences · 2026Article
- Gene- and domain-aware calibration increases the clinical utility of variant effect predictors.Research square · 2026Article
- Massively parallel functional genomic assays in endocrinology: from promise to delivery.Journal of molecular endocrinology · 2026Review
- Determining the intra-residue correlation of missense variant impact using MAVE scores: implications for the ACMG/AMP PM5 criterion for DNA variant classification.Genome medicine · 2026Article
- Gene Portals: A Framework for Integrating Clinical, Functional, and Structural Evidence into Rare Disease Variant Classification.medRxiv : the preprint server for health sciences · 2026Article
- Disease- and gene-specific deep learning for pathogenicity prediction of rare missense variants in cancer predisposition genes.BioData mining · 2026Article
- Creating an atlas of variant effects to resolve variants of uncertain significance and guide cardiovascular medicine.Nature reviews. Cardiology · 2026Review
- A scalable approach to resolving variants of uncertain significance.bioRxiv : the preprint server for biology · 2026Article
- An integrated, scaled approach to resolve TSC2 variants of uncertain significance.bioRxiv : the preprint server for biology · 2026Article
- ClinMAVE: a curated database for clinical application of data from multiplexed assays of variant effect.Nucleic acids research · 2026Article
- The Performance ofHuman mutation · 2026Article
- Reclassification of missense variant pathogenicity using ClinGen recommendations for recalibrated PP3/BP4 in silico predictor score thresholds.Genetics in medicine open · 2026Article
- The genetic architecture of Parkinson's disease on the Island of Crete.NPJ Parkinson's disease · 2025Article
- Proteome-wide model for human disease genetics.Nature genetics · 2025Article
- Calibrated Variant Effect Prediction at the Residue Level Using Conditional Score Distributions.bioRxiv : the preprint server for biology · 2025Article
- acmgscaler: an R package and Colab for standardized gene-level variant effect score calibration within the ACMG/AMP framework.Bioinformatics (Oxford, England) · 2025Article
- Calibration of additional computational tools expands ClinGen recommendation options for variant classification with PP3/BP4 criteria.Genetics in medicine : official journal of the American College of Medical Genetics · 2025Article
- Gene-based calibration of high-throughput functional assays for clinical variant classification.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
In silico variant effect predictions are available for nearly all missense variants but played a minimal role in clinical variant classification because they were deemed to provide only supporting evidence. Recently, the ClinGen Sequence Variant Interpretation (SVI) Working Group updated recommendations for variant effect prediction use. By analyzing control pathogenic and benign variants across all genes, they were able to compute evidence strength for predictor score intervals with some intervals generating moderate, strong, or even very strong evidence. However, this genome-wide approach could obscure heterogeneous predictor performance in different genes. We quantified the gene-by-gene performance of two top predictors, REVEL and BayesDel, by analyzing control variants in each predictor score interval in 3,668 disease-relevant genes. Approximately 10% of intervals had sufficient control variants for analysis, and ∼70% of these intervals exceeded the maximum number of incorrect predictions implied by the SVI recommendations. These trending discordant intervals arose owing to the divergence of the gene-specific distribution of predictions from the genome-wide distribution, suggesting that gene-specific calibration is needed in many cases. Approximately 22% of ClinVar missense variants of uncertain significance in genes we analyzed (REVEL = 100,629, BayesDel = 71,928) had predictions in trending discordant intervals. Thus, genome-wide calibrations could result in many variants receiving inappropriate evidence strength. To facilitate a review of the SVI's calibrations, we developed a web application enabling visualization of gene-specific predictions and trending concordant and discordant intervals.
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