Article

MetaSplice: an ensemble pathogenicity predictor for intronic splice variants

2026-07-27

Abstract excerpt

Splice-altering variants cause an estimated 15-30% of genetic diseases, yet computational tools lose accuracy outside the canonical GT-AG dinucleotides, leaving intronic variants of uncertain significance (VUS) hard to interpret. Here we present MetaSplice, a 53-feature gradient-boosted ensemble integrating deep-learning splice predictions (SpliceTransformer, Pangolin), evolutionary and gene-level constraint, and...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 9ead5d97-170e-5fb3-822f-d7cda2dcaed1
DOI: 10.64898/2026.07.23.740393

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

MetaSplice: an ensemble pathogenicity predictor for intronic splice variantsDOI 10.64898/2026.07.23.740393Read

PDIVAS: Pathogenicity predictor for Deep-Intronic Variants causing Aberrant SplicingSemantic proximity Read

PDIVAS: Pathogenicity predictor for Deep-Intronic Variants causing Aberrant Splicing.Semantic proximity Read

Pathogenicity prediction for noncanonical splice-altering variants based on multimodal feature fusion.Semantic proximity Read

Analyzing the Performance of Deep Learning Splice Prediction AlgorithmsSemantic proximity Read

Introme accurately predicts the impact of coding and noncoding variants on gene splicing, with clinical applications.Semantic proximity Read

CI-SpliceAI-Improving machine learning predictions of disease causing splicing variants using curated alternative splice sites.Semantic proximity Read

SpliceTransformer predicts tissue-specific splicing linked to human diseases.Semantic proximity Read

Computational prediction of human deep intronic variationSemantic proximity Read

Computational prediction of human deep intronic variation.Semantic proximity Read

Benchmarking splice variant prediction algorithms using massively parallel splicing assays.Semantic proximity Read

MMSplice: modular modeling improves the predictions of genetic variant effects on splicing.Semantic proximity Read

S-CAP extends clinical-grade pathogenicity prediction to genetic variants that affect RNA splicingSemantic proximity Read