rewirebio.iobenchmarks
Configuration

Legacy Ensemble (Fortier et al. 2026)

N-of-4 vote of VarSeq legacy algorithms; the voting threshold giving the highest balanced accuracy was used

6 evaluations · 24 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

6 evaluations · 24 results. Different protocols are not a single leaderboard.

Sorted by Balanced accuracy (maximum delta score > 0.5 (Legacy Ensemble N > 1)) (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 datasetBalanced accuracy (maximum delta score > 0.5 (Legacy Ensemble N > 1))F1 (maximum delta score > 0.5 (Legacy Ensemble N > 1))Recall (maximum delta score > 0.5 (Legacy Ensemble N > 1))Specificity (maximum delta score > 0.5 (Legacy Ensemble N > 1))Balanced accuracy (maximum delta score classification after legacy-tool pre-filtering (threshold not restated for this dataset))Balanced accuracy (threshold optimised per algorithm for balanced accuracy on this dataset)Balanced accuracy (threshold optimised per gene and algorithm for maximum accuracy (upper bound))F1 (maximum delta score classification after legacy-tool pre-filtering (threshold not restated for this dataset))F1 (threshold optimised per algorithm for balanced accuracy on this dataset)F1 (threshold optimised per gene and algorithm for maximum accuracy (upper bound))Recall (maximum delta score classification after legacy-tool pre-filtering (threshold not restated for this dataset))Recall (threshold optimised per algorithm for balanced accuracy on this dataset)Recall (threshold optimised per gene and algorithm for maximum accuracy (upper bound))Specificity (maximum delta score classification after legacy-tool pre-filtering (threshold not restated for this dataset))Specificity (threshold optimised per algorithm for balanced accuracy on this dataset)Specificity (threshold optimised per gene and algorithm for maximum accuracy (upper bound))
Legacy Ensemble (Fortier et al. 2026)EvaluationSplice-altering variant classification, Barbosa et al. ClinVar intronic SNV benchmark (53,600 variants) (Fortier et al. Table 5), Barbosa et al. ClinVar intronic SNV benchmark (53,600 variants)0.942 (best in column)0.902 (best in column)0.926 (best in column)0.959 (best in column)Not reportedNot reportedNot reportedNot reportedNot reportedNot reportedNot reportedNot reportedNot reportedNot reportedNot reportedNot reported
Legacy Ensemble (Fortier et al. 2026)EvaluationSplice-altering variant classification, CI-SpliceAI benchmark variant set (1,316 variants) (Fortier et al. Table 1), CI-SpliceAI benchmark variant set (1,316 variants)0.7850.7720.730.84Not reportedNot reportedNot reportedNot reportedNot reportedNot reportedNot reportedNot reportedNot reportedNot reportedNot reportedNot reported
Legacy Ensemble (Fortier et al. 2026)EvaluationSplice-altering variant classification, SPiP benchmark variant set (99,601 variants) (Fortier et al. Table 3), SPiP benchmark variant set (99,601 variants)0.7520.2890.5470.956Not reportedNot reportedNot reportedNot reportedNot reportedNot reportedNot reportedNot reportedNot reportedNot reportedNot reportedNot reported
Legacy Ensemble (Fortier et al. 2026)EvaluationSplice-altering variant classification, Barbosa et al. deep intronic pathogenic variants with matched common controls (484 variants) (Fortier et al. Table 4), Barbosa et al. deep intronic pathogenic variants with matched common controls (484 variants)Not reportedNot reportedNot reportedNot reportedNot reported0.785Not reportedNot reported0.778Not reportedNot reported0.752Not reportedNot reported0.818Not reported
Legacy Ensemble (Fortier et al. 2026)EvaluationSplice-altering variant classification, Extended ClinVar benchmark (58,064 variants) (Fortier et al. Table 6), Extended ClinVar benchmark (58,064 variants)Not reportedNot reportedNot reportedNot reported0.809Not reportedNot reported0.684Not reportedNot reported0.832Not reportedNot reported0.787Not reportedNot reported
Legacy Ensemble (Fortier et al. 2026)EvaluationSplice-altering variant classification, Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3) (Fortier et al. Table 2), Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3)Not reportedNot reportedNot reportedNot reportedNot reportedNot reported0.659Not reportedNot reported0.609Not reportedNot reported0.5Not reportedNot reported0.817
All 24 result rows with coverage, uncertainty and sources
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Applied filters: All linked evaluations

Exact evaluated configurations and original reported results
Tested configurationProtocol and datasetFindingEvidence and details
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, Barbosa et al. ClinVar intronic SNV benchmark (53,600 variants) (Fortier et al. Table 5)
Dataset: Barbosa et al. ClinVar intronic SNV benchmark (53,600 variants)
0.942 Balanced accuracy (maximum delta score > 0.5 (Legacy Ensemble N > 1))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the Barbosa et al. ClinVar intronic SNV benchmark (53,600 variants)

rna-splicing-20261011-fortier2026-protocol-barbosa-clinvar

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 5, row 'Legacy Ensemble', column 'Balanced Accuracy'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, Barbosa et al. ClinVar intronic SNV benchmark (53,600 variants) (Fortier et al. Table 5)
Dataset: Barbosa et al. ClinVar intronic SNV benchmark (53,600 variants)
0.902 F1 (maximum delta score > 0.5 (Legacy Ensemble N > 1))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the Barbosa et al. ClinVar intronic SNV benchmark (53,600 variants)

rna-splicing-20261011-fortier2026-protocol-barbosa-clinvar

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 5, row 'Legacy Ensemble', column 'F1'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, Barbosa et al. ClinVar intronic SNV benchmark (53,600 variants) (Fortier et al. Table 5)
Dataset: Barbosa et al. ClinVar intronic SNV benchmark (53,600 variants)
0.926 Recall (maximum delta score > 0.5 (Legacy Ensemble N > 1))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the Barbosa et al. ClinVar intronic SNV benchmark (53,600 variants)

rna-splicing-20261011-fortier2026-protocol-barbosa-clinvar

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 5, row 'Legacy Ensemble', column 'Sensitivity'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, Barbosa et al. ClinVar intronic SNV benchmark (53,600 variants) (Fortier et al. Table 5)
Dataset: Barbosa et al. ClinVar intronic SNV benchmark (53,600 variants)
0.959 Specificity (maximum delta score > 0.5 (Legacy Ensemble N > 1))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the Barbosa et al. ClinVar intronic SNV benchmark (53,600 variants)

rna-splicing-20261011-fortier2026-protocol-barbosa-clinvar

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 5, row 'Legacy Ensemble', column 'Specificity'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, Barbosa et al. deep intronic pathogenic variants with matched common controls (484 variants) (Fortier et al. Table 4)
Dataset: Barbosa et al. deep intronic pathogenic variants with matched common controls (484 variants)
0.785 Balanced accuracy (threshold optimised per algorithm for balanced accuracy on this dataset)
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the Barbosa et al. deep intronic pathogenic variants with matched common controls (484 variants)

rna-splicing-20261011-fortier2026-protocol-barbosa-deep-intronic

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 4, row 'Legacy Ensemble', column 'Balanced Accuracy'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, Barbosa et al. deep intronic pathogenic variants with matched common controls (484 variants) (Fortier et al. Table 4)
Dataset: Barbosa et al. deep intronic pathogenic variants with matched common controls (484 variants)
0.778 F1 (threshold optimised per algorithm for balanced accuracy on this dataset)
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the Barbosa et al. deep intronic pathogenic variants with matched common controls (484 variants)

rna-splicing-20261011-fortier2026-protocol-barbosa-deep-intronic

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 4, row 'Legacy Ensemble', column 'F1'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, Barbosa et al. deep intronic pathogenic variants with matched common controls (484 variants) (Fortier et al. Table 4)
Dataset: Barbosa et al. deep intronic pathogenic variants with matched common controls (484 variants)
0.752 Recall (threshold optimised per algorithm for balanced accuracy on this dataset)
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the Barbosa et al. deep intronic pathogenic variants with matched common controls (484 variants)

rna-splicing-20261011-fortier2026-protocol-barbosa-deep-intronic

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 4, row 'Legacy Ensemble', column 'Sensitivity'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, Barbosa et al. deep intronic pathogenic variants with matched common controls (484 variants) (Fortier et al. Table 4)
Dataset: Barbosa et al. deep intronic pathogenic variants with matched common controls (484 variants)
0.818 Specificity (threshold optimised per algorithm for balanced accuracy on this dataset)
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the Barbosa et al. deep intronic pathogenic variants with matched common controls (484 variants)

rna-splicing-20261011-fortier2026-protocol-barbosa-deep-intronic

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 4, row 'Legacy Ensemble', column 'Specificity'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, CI-SpliceAI benchmark variant set (1,316 variants) (Fortier et al. Table 1)
Dataset: CI-SpliceAI benchmark variant set (1,316 variants)
0.785 Balanced accuracy (maximum delta score > 0.5 (Legacy Ensemble N > 1))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the CI-SpliceAI benchmark variant set (1,316 variants)

rna-splicing-20261011-fortier2026-protocol-ci-spliceai-benchmark

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 1, row 'Legacy Ensemble', column 'Balanced Accuracy'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, CI-SpliceAI benchmark variant set (1,316 variants) (Fortier et al. Table 1)
Dataset: CI-SpliceAI benchmark variant set (1,316 variants)
0.772 F1 (maximum delta score > 0.5 (Legacy Ensemble N > 1))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the CI-SpliceAI benchmark variant set (1,316 variants)

rna-splicing-20261011-fortier2026-protocol-ci-spliceai-benchmark

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 1, row 'Legacy Ensemble', column 'F1'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, CI-SpliceAI benchmark variant set (1,316 variants) (Fortier et al. Table 1)
Dataset: CI-SpliceAI benchmark variant set (1,316 variants)
0.73 Recall (maximum delta score > 0.5 (Legacy Ensemble N > 1))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the CI-SpliceAI benchmark variant set (1,316 variants)

rna-splicing-20261011-fortier2026-protocol-ci-spliceai-benchmark

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 1, row 'Legacy Ensemble', column 'Sensitivity'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, CI-SpliceAI benchmark variant set (1,316 variants) (Fortier et al. Table 1)
Dataset: CI-SpliceAI benchmark variant set (1,316 variants)
0.84 Specificity (maximum delta score > 0.5 (Legacy Ensemble N > 1))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the CI-SpliceAI benchmark variant set (1,316 variants)

rna-splicing-20261011-fortier2026-protocol-ci-spliceai-benchmark

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 1, row 'Legacy Ensemble', column 'Specificity'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, Extended ClinVar benchmark (58,064 variants) (Fortier et al. Table 6)
Dataset: Extended ClinVar benchmark (58,064 variants)
0.809 Balanced accuracy (maximum delta score classification after legacy-tool pre-filtering (threshold not restated for this dataset))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the Extended ClinVar benchmark (58,064 variants)

rna-splicing-20261011-fortier2026-protocol-extended-clinvar

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 6, row 'Legacy Ensemble', column 'Balanced Accuracy'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, Extended ClinVar benchmark (58,064 variants) (Fortier et al. Table 6)
Dataset: Extended ClinVar benchmark (58,064 variants)
0.684 F1 (maximum delta score classification after legacy-tool pre-filtering (threshold not restated for this dataset))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the Extended ClinVar benchmark (58,064 variants)

rna-splicing-20261011-fortier2026-protocol-extended-clinvar

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 6, row 'Legacy Ensemble', column 'F1'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, Extended ClinVar benchmark (58,064 variants) (Fortier et al. Table 6)
Dataset: Extended ClinVar benchmark (58,064 variants)
0.832 Recall (maximum delta score classification after legacy-tool pre-filtering (threshold not restated for this dataset))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the Extended ClinVar benchmark (58,064 variants)

rna-splicing-20261011-fortier2026-protocol-extended-clinvar

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 6, row 'Legacy Ensemble', column 'Sensitivity'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, Extended ClinVar benchmark (58,064 variants) (Fortier et al. Table 6)
Dataset: Extended ClinVar benchmark (58,064 variants)
0.787 Specificity (maximum delta score classification after legacy-tool pre-filtering (threshold not restated for this dataset))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the Extended ClinVar benchmark (58,064 variants)

rna-splicing-20261011-fortier2026-protocol-extended-clinvar

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 6, row 'Legacy Ensemble', column 'Specificity'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3) (Fortier et al. Table 2)
Dataset: Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3)
0.659 Balanced accuracy (threshold optimised per gene and algorithm for maximum accuracy (upper bound))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3)

rna-splicing-20261011-fortier2026-protocol-riepe

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 2, row 'Legacy Ensemble', column 'Balanced Accuracy'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3) (Fortier et al. Table 2)
Dataset: Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3)
0.609 F1 (threshold optimised per gene and algorithm for maximum accuracy (upper bound))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3)

rna-splicing-20261011-fortier2026-protocol-riepe

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 2, row 'Legacy Ensemble', column 'F1'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3) (Fortier et al. Table 2)
Dataset: Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3)
0.5 Recall (threshold optimised per gene and algorithm for maximum accuracy (upper bound))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3)

rna-splicing-20261011-fortier2026-protocol-riepe

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 2, row 'Legacy Ensemble', column 'Sensitivity'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3) (Fortier et al. Table 2)
Dataset: Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3)
0.817 Specificity (threshold optimised per gene and algorithm for maximum accuracy (upper bound))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3)

rna-splicing-20261011-fortier2026-protocol-riepe

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 2, row 'Legacy Ensemble', column 'Specificity'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, SPiP benchmark variant set (99,601 variants) (Fortier et al. Table 3)
Dataset: SPiP benchmark variant set (99,601 variants)
0.752 Balanced accuracy (maximum delta score > 0.5 (Legacy Ensemble N > 1))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the SPiP benchmark variant set (99,601 variants)

rna-splicing-20261011-fortier2026-protocol-spip

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 3, row 'Legacy Ensemble', column 'Balanced Accuracy'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, SPiP benchmark variant set (99,601 variants) (Fortier et al. Table 3)
Dataset: SPiP benchmark variant set (99,601 variants)
0.289 F1 (maximum delta score > 0.5 (Legacy Ensemble N > 1))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the SPiP benchmark variant set (99,601 variants)

rna-splicing-20261011-fortier2026-protocol-spip

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 3, row 'Legacy Ensemble', column 'F1'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, SPiP benchmark variant set (99,601 variants) (Fortier et al. Table 3)
Dataset: SPiP benchmark variant set (99,601 variants)
0.547 Recall (maximum delta score > 0.5 (Legacy Ensemble N > 1))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the SPiP benchmark variant set (99,601 variants)

rna-splicing-20261011-fortier2026-protocol-spip

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 3, row 'Legacy Ensemble', column 'Sensitivity'
Configuration: Legacy Ensemble (Fortier et al. 2026)Protocol: Splice-altering variant classification, SPiP benchmark variant set (99,601 variants) (Fortier et al. Table 3)
Dataset: SPiP benchmark variant set (99,601 variants)
0.956 Specificity (maximum delta score > 0.5 (Legacy Ensemble N > 1))
fraction · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

Legacy Ensemble on the SPiP benchmark variant set (99,601 variants)

rna-splicing-20261011-fortier2026-protocol-spip

Aggregation: Not reported

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Table 3, row 'Legacy Ensemble', column 'Specificity'

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Stable ID: rna-splicing-20261011-fortier2026-config-legacy-ensemble

areas
dna-genomes
contexts
clinical_research
method types
conventional_pipeline
reported name
Legacy Ensemble
foundation model eligible
false
parameters
Vote threshold N > 1, except N > 0 for the Barbosa deep intronic set and N > 2 for ABCA4 in the Riepe set
access reuse
Algorithms provided by the commercial VarSeq software
source locator
Methods 'Splice prediction tools' and the list of options for the deep learning algorithms
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