Evidence claim

Relevance of ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3) to "Prioritise variants for splicing experiments"

Use case: Prioritise variants for splicing experiments
Assessed by: ABCA4 noncanonical splice-site variants: classification against mini- or midigene splicing results (Riepe et al. Table 3)
Relevance: Proxy evidence
Endpoint: Confusion matrix, accuracy, PPV, sensitivity, specificity, NPV and MCC for up to 11 splice predictors on 71 ABCA4 noncanonical splice-site variants tested in mini- or midigene assays

Experimentally measured splicing of human SNVs, with several predictors scored on the same variants, informs which configurations to use when choosing SNVs for a follow-up splicing experiment. As for the existing MFASS mappings, transfer to a different assay, exon or follow-up capacity is not established.

11 reviewed evaluations

Evidence

Source checking verifies the cited claim or transcription. It does not establish independent reproduction.

Evidence table

Inspect claims, sources and review details

Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.

One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.

20 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-11-02-a7f03c9e55a5
Property and statement	Original source and location	Review and provenance
Citation locations 1 values source id splicing-follow-up-20261009-source-riepe2021 locator Table 3; Methods 'Datasets' and 'In silico splice prediction tools' Context-only references	Benchmarking deep learning splice prediction tools using functional splice assays Original source ↗ splicing-follow-up-20261009-source-riepe2021: Table 3; Methods 'Datasets' and 'In silico splice prediction tools' Version: Human Mutation 42(7):799, published online 2021-05-20; PMC8360004 full-text XML Retrieved: 2026-10-09T20:52:02Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.citation_locators` Source artifact SHA-256: `595be5360a9d3d421c4d4b6adda30175b4048e1aa0b563eb7afd2b7850277112` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison group riepe2021-minigene Context-only references	Benchmarking deep learning splice prediction tools using functional splice assays Original source ↗ splicing-follow-up-20261009-source-riepe2021: Table 3; Methods 'Datasets' and 'In silico splice prediction tools' Version: Human Mutation 42(7):799, published online 2021-05-20; PMC8360004 full-text XML Retrieved: 2026-10-09T20:52:02Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.comparison_group` Source artifact SHA-256: `595be5360a9d3d421c4d4b6adda30175b4048e1aa0b563eb7afd2b7850277112` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison title ABCA4 and MYBPC3 mini- and midigene variant sets (Riepe et al. 2021) Context-only references	Benchmarking deep learning splice prediction tools using functional splice assays Original source ↗ splicing-follow-up-20261009-source-riepe2021: Table 3; Methods 'Datasets' and 'In silico splice prediction tools' Version: Human Mutation 42(7):799, published online 2021-05-20; PMC8360004 full-text XML Retrieved: 2026-10-09T20:52:02Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.comparison_title` Source artifact SHA-256: `595be5360a9d3d421c4d4b6adda30175b4048e1aa0b563eb7afd2b7850277112` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Constraints 2 values Inspect every linked evaluation's source locator and preserved conflicts before citing a result. Do not combine this mapping's evaluations with any other protocol's results, including the matched and historical MFASS protocols; populations, labels and thresholds differ. Context-only references	Benchmarking deep learning splice prediction tools using functional splice assays Original source ↗ splicing-follow-up-20261009-source-riepe2021: Table 3; Methods 'Datasets' and 'In silico splice prediction tools' Version: Human Mutation 42(7):799, published online 2021-05-20; PMC8360004 full-text XML Retrieved: 2026-10-09T20:52:02Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.constraints` Source artifact SHA-256: `595be5360a9d3d421c4d4b6adda30175b4048e1aa0b563eb7afd2b7850277112` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Endpoint Confusion matrix, accuracy, PPV, sensitivity, specificity, NPV and MCC for up to 11 splice predictors on 71 ABCA4 noncanonical splice-site variants tested in mini- or midigene assays Context-only references	Benchmarking deep learning splice prediction tools using functional splice assays Original source ↗ splicing-follow-up-20261009-source-riepe2021: Table 3; Methods 'Datasets' and 'In silico splice prediction tools' Version: Human Mutation 42(7):799, published online 2021-05-20; PMC8360004 full-text XML Retrieved: 2026-10-09T20:52:02Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.endpoint` Source artifact SHA-256: `595be5360a9d3d421c4d4b6adda30175b4048e1aa0b563eb7afd2b7850277112` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Claimed field links:assessed_by:splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss Context-only references	Benchmarking deep learning splice prediction tools using functional splice assays Original source ↗ splicing-follow-up-20261009-source-riepe2021: Table 3; Methods 'Datasets' and 'In silico splice prediction tools' Version: Human Mutation 42(7):799, published online 2021-05-20; PMC8360004 full-text XML Retrieved: 2026-10-09T20:52:02Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.field` Source artifact SHA-256: `595be5360a9d3d421c4d4b6adda30175b4048e1aa0b563eb7afd2b7850277112` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Headline metric matthews-correlation-coefficient Context-only references	Benchmarking deep learning splice prediction tools using functional splice assays Original source ↗ splicing-follow-up-20261009-source-riepe2021: Table 3; Methods 'Datasets' and 'In silico splice prediction tools' Version: Human Mutation 42(7):799, published online 2021-05-20; PMC8360004 full-text XML Retrieved: 2026-10-09T20:52:02Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.headline_metric` Source artifact SHA-256: `595be5360a9d3d421c4d4b6adda30175b4048e1aa0b563eb7afd2b7850277112` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Limitations 6 values Variants were selected for testing with Alamut tools (ABCA4) or MaxEntScan (MYBPC3), which can favour those tools and their relatives. Cutoffs appear to be tuned on the same data set (Table 2 ROC-optimal thresholds); Tables 3-5 do not state the cutoff, so values may be optimistic. Small single-gene sets with strong class imbalance (ABCA4 NCSS 90% positive, ABCA4 DI 26% positive). Variants are from patients but splicing was measured in mini- or midigene assays in HEK293T, not in patient tissue. The authors note the selection bias but observed the opposite pattern (Alamut 3/4 best on MYBPC3). Spidex's unscored variants are counted in its confusion matrix without a stated class. Context-only references	Benchmarking deep learning splice prediction tools using functional splice assays Original source ↗ splicing-follow-up-20261009-source-riepe2021: Table 3; Methods 'Datasets' and 'In silico splice prediction tools' Version: Human Mutation 42(7):799, published online 2021-05-20; PMC8360004 full-text XML Retrieved: 2026-10-09T20:52:02Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.limitations` Source artifact SHA-256: `595be5360a9d3d421c4d4b6adda30175b4048e1aa0b563eb7afd2b7850277112` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
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attributes.numeric_value sha256 6659846540e7f7e0fbf42a564be71ad0c7642099d6fc46e2478d16fb9f0ab802 record id splicing-follow-up-20261009-result-riepe2021-abca4-ncss-splicesitefinder-like-sensitivity fields status attributes.metric attributes.metric_qualifier attributes.printed_value attributes.numeric_value sha256 86e48c3f6077c75ff9de54fddf929892cbcb19a76f2254ad3c55c14b823d8325 record id splicing-follow-up-20261009-result-riepe2021-abca4-ncss-splicesitefinder-like-specificity fields status attributes.metric attributes.metric_qualifier attributes.printed_value attributes.numeric_value sha256 0f2a40bbabb4784769d60e98413c101ad5b4fd2e373076464ee80977295d5766 record id splicing-follow-up-20261009-result-riepe2021-abca4-ncss-splicesitefinder-like-tn fields status attributes.metric attributes.metric_qualifier attributes.printed_value attributes.numeric_value sha256 4d2c6b011ea8458b6ceb6593906d849f61a613c8c067f3b997c1d46e468fe6ba record id splicing-follow-up-20261009-result-riepe2021-abca4-ncss-splicesitefinder-like-tp fields status attributes.metric attributes.metric_qualifier attributes.printed_value attributes.numeric_value sha256 91c40486318ce74009728e34abfa06046ae7c692c3ecaf20a185c79d75f0dcd3 record id splicing-follow-up-20261009-source-riepe2021 fields status attributes.artifact_sha256 sha256 c72ff08c9e91d597a535e8c71142e90884d0b1e3bfb1a62c8cd69e2ea1aa6d40 record id use-case-splicing-follow-up fields status name description facets attributes.question attributes.decision attributes.inputs attributes.output attributes.exclusions attributes.setting attributes.clinical_scope attributes.intended_users sha256 a811d697e1ee1733fb4ed295b0083737c626980c1af83116dc2e404cbf01821b Context-only references	Benchmarking deep learning splice prediction tools using functional splice assays Original source ↗ splicing-follow-up-20261009-source-riepe2021: Table 3; Methods 'Datasets' and 'In silico splice prediction tools' Version: Human Mutation 42(7):799, published online 2021-05-20; PMC8360004 full-text XML Retrieved: 2026-10-09T20:52:02Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.pins` Source artifact SHA-256: `595be5360a9d3d421c4d4b6adda30175b4048e1aa0b563eb7afd2b7850277112` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Rationale Experimentally measured splicing of human SNVs, with several predictors scored on the same variants, informs which configurations to use when choosing SNVs for a follow-up splicing experiment. As for the existing MFASS mappings, transfer to a different assay, exon or follow-up capacity is not established. Context-only references	Benchmarking deep learning splice prediction tools using functional splice assays Original source ↗ splicing-follow-up-20261009-source-riepe2021: Table 3; Methods 'Datasets' and 'In silico splice prediction tools' Version: Human Mutation 42(7):799, published online 2021-05-20; PMC8360004 full-text XML Retrieved: 2026-10-09T20:52:02Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.rationale` Source artifact SHA-256: `595be5360a9d3d421c4d4b6adda30175b4048e1aa0b563eb7afd2b7850277112` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact

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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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Stable ID: use-case-mapping-splicing-follow-up-20261009-riepe2021-abca4-ncss

field: links:assessed_by:splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss
value: splicing-follow-up-20261009-protocol-riepe2021-abca4-ncss
relevance: proxy
endpoint: Confusion matrix, accuracy, PPV, sensitivity, specificity, NPV and MCC for up to 11 splice predictors on 71 ABCA4 noncanonical splice-site variants tested in mini- or midigene assays
rationale: Experimentally measured splicing of human SNVs, with several predictors scored on the same variants, informs which configurations to use when choosing SNVs for a follow-up splicing experiment. As for the existing MFASS mappings, transfer to a different assay, exon or follow-up capacity is not established.
constraints: Inspect every linked evaluation's source locator and preserved conflicts before citing a result.; Do not combine this mapping's evaluations with any other protocol's results, including the matched and historical MFASS protocols; populations, labels and thresholds differ.
limitations: Variants were selected for testing with Alamut tools (ABCA4) or MaxEntScan (MYBPC3), which can favour those tools and their relatives.; Cutoffs appear to be tuned on the same data set (Table 2 ROC-optimal thresholds); Tables 3-5 do not state the cutoff, so values may be optimistic.; Small single-gene sets with strong class imbalance (ABCA4 NCSS 90% positive, ABCA4 DI 26% positive).; Variants are from patients but splicing was measured in mini- or midigene assays in HEK293T, not in patient tissue.; The authors note the selection bias but observed the opposite pattern (Alamut 3/4 best on MYBPC3).; Spidex's unscored variants are counted in its confusion matrix without a stated class.
citation locators: source id: splicing-follow-up-20261009-source-riepe2021; locator: Table 3; Methods 'Datasets' and 'In silico splice prediction tools'
source locator: splicing-follow-up-20261009-source-riepe2021: Table 3; Methods 'Datasets' and 'In silico splice prediction tools'
revision: 1
reason: Recorded from the splicing follow-up use-case pass 2026-10-09 (data/omics/use-case-coverage-splicing-follow-up-20261009/).
comparison group: riepe2021-minigene
comparison title: ABCA4 and MYBPC3 mini- and midigene variant sets (Riepe et al. 2021)
headline metric: matthews-correlation-coefficient
stratum label: ABCA4 noncanonical splice-site variants
stratum order: 1
reviewed evaluations: splicing-follow-up-20261009-eval-riepe2021-abca4-ncss-alamut-consensus; splicing-follow-up-20261009-eval-riepe2021-abca4-ncss-cadd-1-6; splicing-follow-up-20261009-eval-riepe2021-abca4-ncss-dssp; splicing-follow-up-20261009-eval-riepe2021-abca4-ncss-genesplicer; splicing-follow-up-20261009-eval-riepe2021-abca4-ncss-maxentscan; splicing-follow-up-20261009-eval-riepe2021-abca4-ncss-mmsplice-2-0-0; splicing-follow-up-20261009-eval-riepe2021-abca4-ncss-nnsplice; splicing-follow-up-20261009-eval-riepe2021-abca4-ncss-spidex-1-0; splicing-follow-up-20261009-eval-riepe2021-abca4-ncss-spliceai-1-3-1; splicing-follow-up-20261009-eval-riepe2021-abca4-ncss-splicerover; splicing-follow-up-20261009-eval-riepe2021-abca4-ncss-splicesitefinder-like
review: method: automated-source-review; reviewer: claude; reviewer note: Separate Claude review agent, independent of the extractor; no human review claimed; reviewed at: 2026-10-09T22:30:00Z; note: Independent review of endpoint fit, relevance grade, limitations and grouping against the use case and the source text; every value of the listed evaluations was checked against the pinned table. No execution, reproduction, human scientific review or clinical validation.
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subject: Prioritise variants for splicing experiments

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