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SpliceAI (Riepe et al. 2021)

SpliceAI (Riepe et al. 2021) as run in the cited comparison.

Overview

SpliceAI (Riepe et al. 2021) as run in the cited comparison.

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

Evaluations and results

3 evaluations · 33 results. Different protocols are not a single leaderboard.

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Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: SpliceAI (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)	94% accuracy percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'Accuracy (%)'
Configuration: SpliceAI (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)	2 false-negative-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'FN'
Configuration: SpliceAI (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)	3 false-positive-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'FP'
Configuration: SpliceAI (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)	0.84 matthews-correlation-coefficient unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'MCC'
Configuration: SpliceAI (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 count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'Missing values'
Configuration: SpliceAI (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)	97% negative-predictive-value percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'NPV (%)'
Configuration: SpliceAI (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)	86% precision percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'PPV (%)'
Configuration: SpliceAI (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)	90% recall percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'Sensitivity (%)'
Configuration: SpliceAI (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)	95% specificity percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'Specificity (%)'
Configuration: SpliceAI (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)	57 true-negative-count count · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'TN'
Configuration: SpliceAI (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 true-positive-count count · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'TP'
Configuration: SpliceAI (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 checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'Accuracy (%)'
Configuration: SpliceAI (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 false-negative-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'FN'
Configuration: SpliceAI (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)	1 false-positive-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'FP'
Configuration: SpliceAI (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)	0.42 matthews-correlation-coefficient unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'MCC'
Configuration: SpliceAI (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 checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'Missing values'
Configuration: SpliceAI (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)	30% negative-predictive-value percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'NPV (%)'
Configuration: SpliceAI (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)	98% precision percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'PPV (%)'
Configuration: SpliceAI (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)	78% recall percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'Sensitivity (%)'
Configuration: SpliceAI (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)	86% specificity percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'Specificity (%)'
Configuration: SpliceAI (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)	6 true-negative-count count · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'TN'
Configuration: SpliceAI (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)	50 true-positive-count count · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'TP'
Configuration: SpliceAI (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)	67% accuracy percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'Accuracy (%)'
Configuration: SpliceAI (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-negative-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'FN'
Configuration: SpliceAI (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)	8 false-positive-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceAI 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 'SpliceAI', column 'FP'

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Benchmarking deep learning splice prediction tools using functional splice assays · Original source · Human Mutation 42(7):799, published online 2021-05-20; PMC8360004 full-text XML

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Technical metadata and extraction receipts

Stable ID: splicing-follow-up-20261009-config-riepe2021-spliceai-1-3-1

areas: dna-genomes
contexts: research
method types: supervised_machine_learning
reported name: SpliceAI (Riepe et al. 2021)
foundation model eligible: false
version: v1.3.1
parameters: Classification cutoff per data set; Table 2 prints the ROC-optimal thresholds, and Tables 3-5 do not restate which cutoff was applied
source locator: Methods 'In silico splice prediction tools'; Table 2

Related records

configuration of: SpliceAI
system: SpliceAI on ABCA4 deep-intronic variants
system: SpliceAI on ABCA4 noncanonical splice-site variants
system: SpliceAI on MYBPC3 noncanonical splice-site variants

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