| Configuration: Alamut Consensus 3/4 (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 56% accuracy percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceAlamut Consensus 3/4 on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'Alamut Consensus 3/4', column 'Accuracy (%)' |
|---|
| Configuration: Alamut Consensus 3/4 (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 29 false-negative-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceAlamut Consensus 3/4 on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'Alamut Consensus 3/4', column 'FN' |
|---|
| Configuration: Alamut Consensus 3/4 (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 2 false-positive-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceAlamut Consensus 3/4 on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'Alamut Consensus 3/4', column 'FP' |
|---|
| Configuration: Alamut Consensus 3/4 (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 0.16 matthews-correlation-coefficient unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceAlamut Consensus 3/4 on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'Alamut Consensus 3/4', column 'MCC' |
|---|
| Configuration: Alamut Consensus 3/4 (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 0 count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceAlamut Consensus 3/4 on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'Alamut Consensus 3/4', column 'Missing values' |
|---|
| Configuration: Alamut Consensus 3/4 (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 15% negative-predictive-value percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceAlamut Consensus 3/4 on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'Alamut Consensus 3/4', column 'NPV (%)' |
|---|
| Configuration: Alamut Consensus 3/4 (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 95% precision percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceAlamut Consensus 3/4 on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'Alamut Consensus 3/4', column 'PPV (%)' |
|---|
| Configuration: Alamut Consensus 3/4 (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 55% recall percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceAlamut Consensus 3/4 on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'Alamut Consensus 3/4', column 'Sensitivity (%)' |
|---|
| Configuration: Alamut Consensus 3/4 (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 71% specificity percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceAlamut Consensus 3/4 on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'Alamut Consensus 3/4', column 'Specificity (%)' |
|---|
| Configuration: Alamut Consensus 3/4 (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 5 true-negative-count count · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceAlamut Consensus 3/4 on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'Alamut Consensus 3/4', column 'TN' |
|---|
| Configuration: Alamut Consensus 3/4 (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 35 true-positive-count count · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceAlamut Consensus 3/4 on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'Alamut Consensus 3/4', column 'TP' |
|---|
| Configuration: CADD (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 62% accuracy percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCADD on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'CADD', column 'Accuracy (%)' |
|---|
| Configuration: CADD (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 24 false-negative-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCADD on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'CADD', column 'FN' |
|---|
| Configuration: CADD (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 3 false-positive-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCADD on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'CADD', column 'FP' |
|---|
| Configuration: CADD (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 0.12 matthews-correlation-coefficient unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCADD on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'CADD', column 'MCC' |
|---|
| Configuration: CADD (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 0 count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCADD on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'CADD', column 'Missing values' |
|---|
| Configuration: CADD (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 14% negative-predictive-value percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCADD on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'CADD', column 'NPV (%)' |
|---|
| Configuration: CADD (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 93% precision percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCADD on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'CADD', column 'PPV (%)' |
|---|
| Configuration: CADD (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 63% recall percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCADD on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'CADD', column 'Sensitivity (%)' |
|---|
| Configuration: CADD (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 57% specificity percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCADD on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'CADD', column 'Specificity (%)' |
|---|
| Configuration: CADD (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 4 true-negative-count count · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCADD on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'CADD', column 'TN' |
|---|
| Configuration: CADD (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 40 true-positive-count count · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCADD on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'CADD', column 'TP' |
|---|
| Configuration: DSSP (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 79% accuracy percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDSSP on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'DSSP', column 'Accuracy (%)' |
|---|
| Configuration: DSSP (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 13 false-negative-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDSSP on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'DSSP', column 'FN' |
|---|
| Configuration: DSSP (Riepe et al. 2021) | Protocol: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Dataset: ABCA4 noncanonical splice-site variants (Riepe et al. benchmark set) | 2 false-positive-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDSSP on ABCA4 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 3 row 'DSSP', column 'FP' |
|---|