rewirebio.iobenchmarks
Configuration

Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)

Exomiser 12.1.0 'Exomiser score' gene ranking: Weighted combination of ExomeWalker, PHIVE and PhenIX gene scores; a random variant generated in each candidate gene; variant scores ignored; default settings.

2 evaluations · 40 results

Overview

An explanatory profile has not yet been reviewed for this record.

Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.

Evaluations and results

2 evaluations · 40 results. Different protocols are not a single leaderboard.

Sorted by AUPRC (candidate gene set of 100 genes including the causative gene) (higher is better). The best value in each column is highlighted. Decimals are rounded for display; each value links to the printed value and its source.

Tested configurationProtocol and datasetAUPRC (candidate gene set of 100 genes including the causative gene)AUPRC (candidate gene set of 25 genes including the causative gene)AUPRC (candidate gene set of 5 genes including the causative gene)AUPRC (candidate gene set of 50 genes including the causative gene)AUPRC (candidate gene set of 75 genes including the causative gene)AUROC (candidate gene set of 100 genes including the causative gene)AUROC (candidate gene set of 25 genes including the causative gene)AUROC (candidate gene set of 5 genes including the causative gene)AUROC (candidate gene set of 50 genes including the causative gene)AUROC (candidate gene set of 75 genes including the causative gene)Top-1 accuracy (candidate gene set of 100 genes including the causative gene)Top-1 accuracy (candidate gene set of 25 genes including the causative gene)Top-1 accuracy (candidate gene set of 5 genes including the causative gene)Top-1 accuracy (candidate gene set of 50 genes including the causative gene)Top-1 accuracy (candidate gene set of 75 genes including the causative gene)Top-10 accuracy (candidate gene set of 100 genes including the causative gene)Top-10 accuracy (candidate gene set of 25 genes including the causative gene)Top-10 accuracy (candidate gene set of 5 genes including the causative gene)Top-10 accuracy (candidate gene set of 50 genes including the causative gene)Top-10 accuracy (candidate gene set of 75 genes including the causative gene)
Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)EvaluationRanking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3), ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)0.766 (best in column)0.799 (best in column)0.889 (best in column)0.789 (best in column)0.771 (best in column)0.93 (best in column)0.938 (best in column)0.967 (best in column)0.936 (best in column)0.932 (best in column)82% (best in column)84% (best in column)89%84% (best in column)82% (best in column)85% (best in column)91% (best in column)100% (best in column)91% (best in column)86% (best in column)
Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)EvaluationRanking the causative gene within synthetic candidate sets of 5 to 100 genes, PAVS (Kafkas et al. 2025 Table 3), PAVS Saudi phenotype-associated variants, 500 genes (Kafkas et al. 2025)0.4450.6180.7710.540.4830.870.880.9270.8750.87258.6%65.6%97.6% (best in column)57.2%51.6%78.4%82.6%100% (best in column)80.2%79.4%
All 40 result rows with coverage, uncertainty and sources
Filter evaluations

Applied filters: All linked evaluations

Exact evaluated configurations and original reported results
Tested configurationProtocol and datasetFindingEvidence and details
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
0.766 AUPRC (candidate gene set of 100 genes including the causative gene)
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 100, 'AUPR', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
0.93 AUROC (candidate gene set of 100 genes including the causative gene)
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 100, 'ROC AUC', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
82% Top-1 accuracy (candidate gene set of 100 genes including the causative gene)
percent · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 100, 'Hits@1 (%)', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
85% Top-10 accuracy (candidate gene set of 100 genes including the causative gene)
percent · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 100, 'Hits@10 (%)', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
0.799 AUPRC (candidate gene set of 25 genes including the causative gene)
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 25, 'AUPR', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
0.938 AUROC (candidate gene set of 25 genes including the causative gene)
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 25, 'ROC AUC', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
84% Top-1 accuracy (candidate gene set of 25 genes including the causative gene)
percent · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 25, 'Hits@1 (%)', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
91% Top-10 accuracy (candidate gene set of 25 genes including the causative gene)
percent · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 25, 'Hits@10 (%)', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
0.889 AUPRC (candidate gene set of 5 genes including the causative gene)
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 5, 'AUPR', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
0.967 AUROC (candidate gene set of 5 genes including the causative gene)
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 5, 'ROC AUC', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
89% Top-1 accuracy (candidate gene set of 5 genes including the causative gene)
percent · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 5, 'Hits@1 (%)', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
100% Top-10 accuracy (candidate gene set of 5 genes including the causative gene)
percent · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 5, 'Hits@10 (%)', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
0.789 AUPRC (candidate gene set of 50 genes including the causative gene)
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 50, 'AUPR', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
0.936 AUROC (candidate gene set of 50 genes including the causative gene)
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 50, 'ROC AUC', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
84% Top-1 accuracy (candidate gene set of 50 genes including the causative gene)
percent · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 50, 'Hits@1 (%)', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
91% Top-10 accuracy (candidate gene set of 50 genes including the causative gene)
percent · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 50, 'Hits@10 (%)', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
0.771 AUPRC (candidate gene set of 75 genes including the causative gene)
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 75, 'AUPR', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
0.932 AUROC (candidate gene set of 75 genes including the causative gene)
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 75, 'ROC AUC', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
82% Top-1 accuracy (candidate gene set of 75 genes including the causative gene)
percent · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 75, 'Hits@1 (%)', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, ClinVar (Kafkas et al. 2025 Table 3)
Dataset: ClinVar variants added 2 July to 7 October 2023, 100 genes (Kafkas et al. 2025)
86% Top-10 accuracy (candidate gene set of 75 genes including the causative gene)
percent · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on ClinVar candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-clinvar-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 75, 'Hits@10 (%)', column 'ClinVar' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, PAVS (Kafkas et al. 2025 Table 3)
Dataset: PAVS Saudi phenotype-associated variants, 500 genes (Kafkas et al. 2025)
0.445 AUPRC (candidate gene set of 100 genes including the causative gene)
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on PAVS candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-pavs-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 100, 'AUPR', column 'PAVS' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, PAVS (Kafkas et al. 2025 Table 3)
Dataset: PAVS Saudi phenotype-associated variants, 500 genes (Kafkas et al. 2025)
0.87 AUROC (candidate gene set of 100 genes including the causative gene)
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on PAVS candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-pavs-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 100, 'ROC AUC', column 'PAVS' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, PAVS (Kafkas et al. 2025 Table 3)
Dataset: PAVS Saudi phenotype-associated variants, 500 genes (Kafkas et al. 2025)
58.6% Top-1 accuracy (candidate gene set of 100 genes including the causative gene)
percent · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on PAVS candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-pavs-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 100, 'Hits@1 (%)', column 'PAVS' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, PAVS (Kafkas et al. 2025 Table 3)
Dataset: PAVS Saudi phenotype-associated variants, 500 genes (Kafkas et al. 2025)
78.4% Top-10 accuracy (candidate gene set of 100 genes including the causative gene)
percent · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on PAVS candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-pavs-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 100, 'Hits@10 (%)', column 'PAVS' 'Exomiser'
Configuration: Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)Protocol: Ranking the causative gene within synthetic candidate sets of 5 to 100 genes, PAVS (Kafkas et al. 2025 Table 3)
Dataset: PAVS Saudi phenotype-associated variants, 500 genes (Kafkas et al. 2025)
0.618 AUPRC (candidate gene set of 25 genes including the causative gene)
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Exomiser on PAVS candidate gene sets

rare-ranking-20261009-protocol-kafkas2025-pavs-gene-sets

Aggregation: Not reported

The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients · Table 3 row Size 25, 'AUPR', column 'PAVS' 'Exomiser'

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Technical metadata and extraction receipts

Stable ID: rare-ranking-20261009-config-kafkas2025-exomiser-12-1-0

areas
dna-genomes
contexts
clinical_research
method types
conventional_pipeline
reported name
Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025)
foundation model eligible
false
version
12.1.0
parameters
Weighted combination of ExomeWalker, PHIVE and PhenIX gene scores; a random variant generated in each candidate gene; variant scores ignored; default settings
source locator
Methods 'Baseline methods'
provenance note
Exomiser 12.1.0 'Exomiser score' gene ranking (Kafkas et al. 2025) as evaluated in the cited comparison.
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