ArticleGenome medicine2020
CAPICE: a computational method for Consequence-Agnostic Pathogenicity Interpretation of Clinical Exome variations.
Article in Genome medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed.
- aiDIVA - hybrid AI for rare disease diagnostics using evidence-based, machine learning and language models.NPJ genomic medicine · 2026Article
- BICEP: an extension to indels and copy number variants for rare variant prioritisation in pedigree analysis.bioRxiv : the preprint server for biology · 2026Article
- Accelerating rare disease diagnostics by linking DNA and RNA through an explainable and interactive RNA-guided workflow.NAR genomics and bioinformatics · 2026Article
- Identification of novelResearch and practice in thrombosis and haemostasis · 2026Article
- Proteome-Wide Analysis of Human Deletions.Proteins · 2026Article
- Leveraging protein language models and a scoring function for indel characterization and transfer learning.Patterns (New York, N.Y.) · 2026Article
- PON-Del predictor for sequence retaining protein deletions.PLoS computational biology · 2026Article
- Harnessing artificial intelligence for genomic variant prediction: advances, challenges, and future directions.GigaScience · 2026Review
- A multidisciplinary RNA-guided approach to complement genomic analysis of unsolved patients with an inborn error of immunity.Frontiers in immunology · 2026Article
- MutAnt: mutation annotation tool predicts deleteriousness of missense mutations and improves mutation calling from transcriptomics.Human genetics · 2025Article
- Expanding the utility of variant effect predictions with phenotype-specific models.Nature communications · 2025Article
- Prediction of human pathogenic start loss variants based on self-supervised contrastive learning.BMC biology · 2025Article
- Using large-scale population-based data to improve disease risk assessment of clinical variants.Nature genetics · 2025Review
- MOLGENIS VIP: an end-to-end DNA variant interpretation pipeline for research and diagnostics configurable to support rapid implementation of new methods.NAR genomics and bioinformatics · 2025Article
- An exploratory study combining Virtual Reality and Semantic Web for life science research using Graph2VR.Database : the journal of biological databases and curation · 2025Article
- Variant effect predictor correlation with functional assays is reflective of clinical classification performance.Genome biology · 2025Article
- A graph neural network approach for accurate prediction of pathogenicity in multi-type variants.Briefings in bioinformatics · 2025Article
- Tissue-aware interpretation of genetic variants advances the etiology of rare diseases.Molecular systems biology · 2024Article
- VarCards2: an integrated genetic and clinical database for ACMG-AMP variant-interpretation guidelines in the human whole genome.Nucleic acids research · 2024Article
- Widening the infantile hypotonia with psychomotor retardation and characteristic Facies-1 Syndrome's clinical and molecular spectrum through NALCNFrontiers in genetics · 2024Article
Corrections and comments
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Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Exome sequencing is now mainstream in clinical practice. However, identification of pathogenic Mendelian variants remains time-consuming, in part, because the limited accuracy of current computational prediction methods requires manual classification by experts. Here we introduce CAPICE, a new machine-learning-based method for prioritizing pathogenic variants, including SNVs and short InDels. CAPICE outperforms the best general (CADD, GAVIN) and consequence-type-specific (REVEL, ClinPred) computational prediction methods, for both rare and ultra-rare variants. CAPICE is easily added to diagnostic pipelines as pre-computed score file or command-line software, or using online MOLGENIS web service with API. Download CAPICE for free and open-source (LGPLv3) at https://github.com/molgenis/capice .
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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 Socratic graph.