| Configuration: DSSP (Riepe et al. 2021) | Protocol: ABCA4 deep-intronic variants: classification against mini- or midigene splicing results (Riepe et al. Table 4) Dataset: ABCA4 deep-intronic variants (Riepe et al. benchmark set) | 67% 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 deep-intronic variants splicing-follow-up-20261009-protocol-riepe2021-abca4-di Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 4 row 'DSSP', column 'Accuracy (%)' |
|---|
| Configuration: DSSP (Riepe et al. 2021) | Protocol: ABCA4 deep-intronic variants: classification against mini- or midigene splicing results (Riepe et al. Table 4) Dataset: ABCA4 deep-intronic variants (Riepe et al. benchmark set) | 8 False negatives 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 deep-intronic variants splicing-follow-up-20261009-protocol-riepe2021-abca4-di Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 4 row 'DSSP', column 'FN' |
|---|
| Configuration: DSSP (Riepe et al. 2021) | Protocol: ABCA4 deep-intronic variants: classification against mini- or midigene splicing results (Riepe et al. Table 4) Dataset: ABCA4 deep-intronic variants (Riepe et al. benchmark set) | 19 False positives 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 deep-intronic variants splicing-follow-up-20261009-protocol-riepe2021-abca4-di Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 4 row 'DSSP', column 'FP' |
|---|
| Configuration: DSSP (Riepe et al. 2021) | Protocol: ABCA4 deep-intronic variants: classification against mini- or midigene splicing results (Riepe et al. Table 4) Dataset: ABCA4 deep-intronic variants (Riepe et al. benchmark set) | 0.27 MCC unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDSSP on ABCA4 deep-intronic variants splicing-follow-up-20261009-protocol-riepe2021-abca4-di Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 4 row 'DSSP', column 'MCC' |
|---|
| Configuration: DSSP (Riepe et al. 2021) | Protocol: ABCA4 deep-intronic variants: classification against mini- or midigene splicing results (Riepe et al. Table 4) Dataset: ABCA4 deep-intronic variants (Riepe et al. benchmark set) | 0 Count (variants without a score) 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 deep-intronic variants splicing-follow-up-20261009-protocol-riepe2021-abca4-di Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 4 row 'DSSP', column 'Missing values' |
|---|
| Configuration: DSSP (Riepe et al. 2021) | Protocol: ABCA4 deep-intronic variants: classification against mini- or midigene splicing results (Riepe et al. Table 4) Dataset: ABCA4 deep-intronic variants (Riepe et al. benchmark set) | 84% 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 sourceDSSP on ABCA4 deep-intronic variants splicing-follow-up-20261009-protocol-riepe2021-abca4-di Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 4 row 'DSSP', column 'NPV (%)' |
|---|
| Configuration: DSSP (Riepe et al. 2021) | Protocol: ABCA4 deep-intronic variants: classification against mini- or midigene splicing results (Riepe et al. Table 4) Dataset: ABCA4 deep-intronic variants (Riepe et al. benchmark set) | 41% Precision 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 deep-intronic variants splicing-follow-up-20261009-protocol-riepe2021-abca4-di Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 4 row 'DSSP', column 'PPV (%)' |
|---|
| Configuration: DSSP (Riepe et al. 2021) | Protocol: ABCA4 deep-intronic variants: classification against mini- or midigene splicing results (Riepe et al. Table 4) Dataset: ABCA4 deep-intronic variants (Riepe et al. benchmark set) | 62% Recall 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 deep-intronic variants splicing-follow-up-20261009-protocol-riepe2021-abca4-di Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 4 row 'DSSP', column 'Sensitivity (%)' |
|---|
| Configuration: DSSP (Riepe et al. 2021) | Protocol: ABCA4 deep-intronic variants: classification against mini- or midigene splicing results (Riepe et al. Table 4) Dataset: ABCA4 deep-intronic variants (Riepe et al. benchmark set) | 68% Specificity 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 deep-intronic variants splicing-follow-up-20261009-protocol-riepe2021-abca4-di Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 4 row 'DSSP', column 'Specificity (%)' |
|---|
| Configuration: DSSP (Riepe et al. 2021) | Protocol: ABCA4 deep-intronic variants: classification against mini- or midigene splicing results (Riepe et al. Table 4) Dataset: ABCA4 deep-intronic variants (Riepe et al. benchmark set) | 41 True negatives count · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDSSP on ABCA4 deep-intronic variants splicing-follow-up-20261009-protocol-riepe2021-abca4-di Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 4 row 'DSSP', column 'TN' |
|---|
| Configuration: DSSP (Riepe et al. 2021) | Protocol: ABCA4 deep-intronic variants: classification against mini- or midigene splicing results (Riepe et al. Table 4) Dataset: ABCA4 deep-intronic variants (Riepe et al. benchmark set) | 13 True positives count · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDSSP on ABCA4 deep-intronic variants splicing-follow-up-20261009-protocol-riepe2021-abca4-di Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 4 row 'DSSP', 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 negatives 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 positives 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' |
|---|
| 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) | 0.35 MCC unitless · 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 'MCC' |
|---|
| 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) | 0 Count (variants without a score) 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 'Missing values' |
|---|
| 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) | 28% 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 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 'NPV (%)' |
|---|
| 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) | 96% Precision 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 'PPV (%)' |
|---|
| 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) | 80% Recall 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 'Sensitivity (%)' |
|---|
| 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) | 71% Specificity 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 'Specificity (%)' |
|---|
| 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) | 5 True negatives count · 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 'TN' |
|---|
| 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) | 51 True positives count · 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 'TP' |
|---|
| Configuration: DSSP (Riepe et al. 2021) | Protocol: MYBPC3 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 5) Dataset: MYBPC3 noncanonical splice-site variants (Riepe et al. benchmark set) | 64% 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 MYBPC3 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-mybpc3-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 5 row 'DSSP', column 'Accuracy (%)' |
|---|
| Configuration: DSSP (Riepe et al. 2021) | Protocol: MYBPC3 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 5) Dataset: MYBPC3 noncanonical splice-site variants (Riepe et al. benchmark set) | 12 False negatives count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDSSP on MYBPC3 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-mybpc3-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 5 row 'DSSP', column 'FN' |
|---|
| Configuration: DSSP (Riepe et al. 2021) | Protocol: MYBPC3 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 5) Dataset: MYBPC3 noncanonical splice-site variants (Riepe et al. benchmark set) | 10 False positives count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDSSP on MYBPC3 noncanonical splice-site variants splicing-follow-up-20261009-protocol-riepe2021-mybpc3-ncss Aggregation: Not reported Benchmarking deep learning splice prediction tools using functional splice assays · Table 5 row 'DSSP', column 'FP' |
|---|