| Configuration: OpenSpliceAI (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) | 0.965 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'Balanced Accuracy' |
|---|
| Configuration: OpenSpliceAI (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) | 0.961 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'F1' |
|---|
| Configuration: OpenSpliceAI (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) | 0.932 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'Sensitivity' |
|---|
| Configuration: OpenSpliceAI (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) | 0.998 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'Specificity' |
|---|
| Configuration: OpenSpliceAI (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) | 0.841 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'Balanced Accuracy' |
|---|
| Configuration: OpenSpliceAI (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) | 0.815 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'F1' |
|---|
| Configuration: OpenSpliceAI (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) | 0.702 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'Sensitivity' |
|---|
| Configuration: OpenSpliceAI (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) | 0.979 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'Specificity' |
|---|
| Configuration: OpenSpliceAI (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) | 0.895 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'Balanced Accuracy' |
|---|
| Configuration: OpenSpliceAI (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) | 0.886 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'F1' |
|---|
| Configuration: OpenSpliceAI (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) | 0.816 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'Sensitivity' |
|---|
| Configuration: OpenSpliceAI (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) | 0.975 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'Specificity' |
|---|
| Configuration: OpenSpliceAI (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) | 0.895 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'Balanced Accuracy' |
|---|
| Configuration: OpenSpliceAI (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) | 0.877 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'F1' |
|---|
| Configuration: OpenSpliceAI (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) | 0.799 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'Sensitivity' |
|---|
| Configuration: OpenSpliceAI (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) | 0.992 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'Specificity' |
|---|
| Configuration: OpenSpliceAI (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) | 0.746 Balanced accuracy (delta score for each variant's effect type; 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'Balanced Accuracy' |
|---|
| Configuration: OpenSpliceAI (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) | 0.741 F1 (delta score for each variant's effect type; 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'F1' |
|---|
| Configuration: OpenSpliceAI (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) | 0.672 Recall (delta score for each variant's effect type; 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'Sensitivity' |
|---|
| Configuration: OpenSpliceAI (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) | 0.819 Specificity (delta score for each variant's effect type; 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'Specificity' |
|---|
| Configuration: OpenSpliceAI (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) | 0.797 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'Balanced Accuracy' |
|---|
| Configuration: OpenSpliceAI (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) | 0.724 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'F1' |
|---|
| Configuration: OpenSpliceAI (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) | 0.595 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'Sensitivity' |
|---|
| Configuration: OpenSpliceAI (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) | 0.999 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 | Independent external evaluation · Source checkedMethods, coverage and sourceOpenSpliceAI 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 'OpenSpliceAI', column 'Specificity' |
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