Article

PrimateAI-3D outperforms AlphaMissense in real-world cohorts

2024-01-13

Abstract excerpt

Accurately predicting the impact of genetic variants is essential for interpreting genomic data, yet no consensus exists on how to measure classifier performance. We prepared the most comprehensive set of benchmarks to date and applied them to the recently published models PrimateAI-3D and AlphaMissense. PrimateAI-3D outperforms AlphaMissense on rare-disease cohort and biobank benchmarks, indicating that performan...

Topics

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

Identifiers and source

Literature Corpus work: b281b3d8-87fe-5397-ab3e-9e2dd45d220b
DOI: 10.1101/2024.01.12.24301193

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

PrimateAI-3D outperforms AlphaMissense in real-world cohortsDOI 10.1101/2024.01.12.24301193Read

Equitable machine learning counteracts ancestral bias in precision medicine, improving outcomes for allSemantic proximity Read

Genomic heterogeneity inflates the performance of variant pathogenicity predictionsSemantic proximity Read

Calibration of additional computational tools expands ClinGen recommendation options for variant classification with PP3/BP4 criteriaSemantic proximity Read

Causal Prediction of TP53 Variant Pathogenicity Using a Perturbation-Informed Protein Language Model.Semantic proximity Read

Benchmarking computational variant effect predictors by their ability to infer human traits.Semantic proximity Read

CIViC: A knowledgebase for expert-crowdsourcing the clinical interpretation of variants in cancerSemantic proximity Read

PON-P and PON-P2 predictor performance in CAGI challenges: Lessons learned.Semantic proximity Read

Toward Advanced Quantitative Prediction of Missense Variant EffectsSemantic proximity Read

Calibration of additional computational tools expands ClinGen recommendation options for variant classification with PP3/BP4 criteria.Semantic proximity Read

CADD-SV – a framework to score the effects of structural variants in health and diseaseSemantic proximity Read

Systematic assessment of machine learning-based variant annotation methods for rare variant association testingSemantic proximity Read

EIRsurvival: Deep Learning-based time-to-event analysis on high-dimensional genotype and multi-omics dataSemantic proximity Read