Evidence claim

Relevance of Splice-altering variant classification, Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3) (Fortier et al. Table 2) to "Select a patient-RNA splicing-variant validation workflow"

Use case: Select a patient-RNA splicing-variant validation workflow
Assessed by: Splice-altering variant classification, Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3) (Fortier et al. Table 2)
Relevance: Proxy evidence
Endpoint: Sensitivity, specificity, F1 and balanced accuracy of SpliceAI, CI-SpliceAI, OpenSpliceAI and a legacy N-of-4 vote on the Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3)

Proxy: DNA-based splice predictors scored against experimentally established splicing outcomes, the sequence-classification kind of evidence the use case keeps separate from patient-RNA recovery; inputs are variants, not patient RNA-seq.

4 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.

19 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-10-22-1b7cf027e4f6
Property and statement	Original source and location	Review and provenance
Citation locations 1 values source id rna-splicing-20261011-fortier2026-source-article locator Methods 'Riepe benchmark dataset' and 'Splice prediction tools'; Table 2 Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'Riepe benchmark dataset' and 'Splice prediction tools'; Table 2 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.citation_locators` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison group fortier2026-spliceai-reimplementations Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'Riepe benchmark dataset' and 'Splice prediction tools'; Table 2 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.comparison_group` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison title SpliceAI and its open-source reimplementations on six splice benchmarks (Fortier et al. 2026) Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'Riepe benchmark dataset' and 'Splice prediction tools'; Table 2 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.comparison_title` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Constraints 2 values Inspect every linked evaluation's source locator before citing a result. Do not combine this mapping's evaluations with any other protocol's results; variant sets, labels and thresholds differ. Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'Riepe benchmark dataset' and 'Splice prediction tools'; Table 2 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.constraints` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Endpoint Sensitivity, specificity, F1 and balanced accuracy of SpliceAI, CI-SpliceAI, OpenSpliceAI and a legacy N-of-4 vote on the Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3) Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'Riepe benchmark dataset' and 'Splice prediction tools'; Table 2 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.endpoint` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Claimed field links:assessed_by:rna-splicing-20261011-fortier2026-protocol-riepe Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'Riepe benchmark dataset' and 'Splice prediction tools'; Table 2 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.field` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Headline metric balanced-accuracy Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'Riepe benchmark dataset' and 'Splice prediction tools'; Table 2 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.headline_metric` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Limitations 5 values Thresholds optimised on the same data for this benchmark, which may overestimate real-world performance (Discussion 'Study limitations'). Labels and variant sets are reused from earlier publications. CI-SpliceAI was trained on all human chromosomes, so no benchmark variant is held out from its training; ABCA4 lies on a test chromosome held out by both SpliceAI and OpenSpliceAI (Methods 'Technical overview of deep learning methods'; Discussion). No uncertainty intervals are printed; significance is from two-proportion Z-tests on accuracy in the Results. Independent of the SpliceAI, CI-SpliceAI and OpenSpliceAI developers; the authors' employer supplies the Legacy Ensemble software, so those rows are author_reported. Variant-level splicing effect, not pathogenicity or diagnostic yield; tissue context is not modelled. Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'Riepe benchmark dataset' and 'Splice prediction tools'; Table 2 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.limitations` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Pinned records 23 values record id rna-splicing-20261011-fortier2026-eval-riepe-ci-spliceai fields status links attributes.origin attributes.comparison sha256 b98af9f3b073e782e259b7a33d4f2fe5995c3837986a92b10dede1294945d26d record id rna-splicing-20261011-fortier2026-eval-riepe-legacy-ensemble fields status links attributes.origin attributes.comparison sha256 265984b1014a9d1034157a25d2eba958ae4239d80dc6472497ad4e6856f05a65 record id rna-splicing-20261011-fortier2026-eval-riepe-openspliceai fields status links attributes.origin attributes.comparison sha256 7692639eec8dfa0709e2ebeb6fe79b1933bf02efa8d5da24dc5368978f5732eb record id rna-splicing-20261011-fortier2026-eval-riepe-spliceai fields status links attributes.origin attributes.comparison sha256 a3e278c79958b01cf70e85cc1ada32f4ec52fa08cad9c8fbd84b7319c1478119 record id rna-splicing-20261011-fortier2026-protocol-riepe fields status name description facets source_ids links attributes sha256 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b7781cea28e1f33ca926c987bf02635405271731c645dcbaefa0f5ca8f3a69af record id rna-splicing-20261011-fortier2026-result-riepe-openspliceai-specificity fields status attributes.metric attributes.metric_qualifier attributes.printed_value attributes.numeric_value sha256 23f341b4b69334504b9c253a78150f8415af1f548cb43b07e2c2b50bc36b3ae1 record id rna-splicing-20261011-fortier2026-result-riepe-spliceai-balanced-accuracy fields status attributes.metric attributes.metric_qualifier attributes.printed_value attributes.numeric_value sha256 165cc2cd41ec671e365950bb75eef764e9cfcb8f3f5d6273c9032d5e92efc2aa record id rna-splicing-20261011-fortier2026-result-riepe-spliceai-f1-score fields status attributes.metric attributes.metric_qualifier attributes.printed_value attributes.numeric_value sha256 95b5c5749d0587304a731160bf370de19b97b13f0409a3f772aea83e96f080e7 record id rna-splicing-20261011-fortier2026-result-riepe-spliceai-recall fields status attributes.metric attributes.metric_qualifier attributes.printed_value attributes.numeric_value sha256 b99b7d14f580aff11ada71a186cc0540349071d9842292ef0e5a2db8ff85addb record id rna-splicing-20261011-fortier2026-result-riepe-spliceai-specificity fields status attributes.metric attributes.metric_qualifier attributes.printed_value attributes.numeric_value sha256 0b7760eb56432c9c26bb916bcc7735d196c2dee87d9a49668810c34a134c2008 record id rna-splicing-20261011-fortier2026-source-article fields status attributes.artifact_sha256 sha256 f632aac0a971c54f908ad18bc9965d498c05b69bd07552d9915807db55a22233 record id use-case-patient-rna-splicing-validation fields status name description facets attributes.question attributes.decision attributes.inputs attributes.output attributes.exclusions attributes.setting attributes.clinical_scope attributes.intended_users sha256 b85cad56e15fbfad66a2e70c3b193ed56c464e5e44b62a19b12f391e409ec897 Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'Riepe benchmark dataset' and 'Splice prediction tools'; Table 2 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.pins` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Rationale Proxy: DNA-based splice predictors scored against experimentally established splicing outcomes, the sequence-classification kind of evidence the use case keeps separate from patient-RNA recovery; inputs are variants, not patient RNA-seq. Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'Riepe benchmark dataset' and 'Splice prediction tools'; Table 2 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.rationale` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact

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Release 2026-10-22-1b7cf027e4f6 · Record review: source checked

1 source record and release history

Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Original source · PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML

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Technical metadata and extraction receipts

Stable ID: use-case-mapping-rna-splicing-20261011-fortier2026-riepe

field: links:assessed_by:rna-splicing-20261011-fortier2026-protocol-riepe
value: rna-splicing-20261011-fortier2026-protocol-riepe
relevance: proxy
endpoint: Sensitivity, specificity, F1 and balanced accuracy of SpliceAI, CI-SpliceAI, OpenSpliceAI and a legacy N-of-4 vote on the Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3)
rationale: Proxy: DNA-based splice predictors scored against experimentally established splicing outcomes, the sequence-classification kind of evidence the use case keeps separate from patient-RNA recovery; inputs are variants, not patient RNA-seq.
constraints: Inspect every linked evaluation's source locator before citing a result.; Do not combine this mapping's evaluations with any other protocol's results; variant sets, labels and thresholds differ.
limitations: Thresholds optimised on the same data for this benchmark, which may overestimate real-world performance (Discussion 'Study limitations').; Labels and variant sets are reused from earlier publications. CI-SpliceAI was trained on all human chromosomes, so no benchmark variant is held out from its training; ABCA4 lies on a test chromosome held out by both SpliceAI and OpenSpliceAI (Methods 'Technical overview of deep learning methods'; Discussion).; No uncertainty intervals are printed; significance is from two-proportion Z-tests on accuracy in the Results.; Independent of the SpliceAI, CI-SpliceAI and OpenSpliceAI developers; the authors' employer supplies the Legacy Ensemble software, so those rows are author_reported.; Variant-level splicing effect, not pathogenicity or diagnostic yield; tissue context is not modelled.
citation locators: source id: rna-splicing-20261011-fortier2026-source-article; locator: Methods 'Riepe benchmark dataset' and 'Splice prediction tools'; Table 2
source locator: rna-splicing-20261011-fortier2026-source-article: Methods 'Riepe benchmark dataset' and 'Splice prediction tools'; Table 2
headline metric: balanced-accuracy
comparison group: fortier2026-spliceai-reimplementations
comparison title: SpliceAI and its open-source reimplementations on six splice benchmarks (Fortier et al. 2026)
stratum label: Riepe et al. functional splice assay variants (213 variants, ABCA4 and MYBPC3)
stratum order: 2
reason: Recorded from the 2026-10-11 use-case literature pass (data/omics/use-case-coverage-rna-splicing-20261011-fortier2026). Independently reviewed in docs/reviews/use-cases/splicing-cnv-use-cases-2026-10-12.md.
review: method: source-hash-verification; independent-cell-check; automated-source-review; scope-review; reviewer: claude; reviewer note: Independent Claude review agent reviewer-scnv; did not extract this batch; no human review claimed; date: 2026-10-12; artifact sha256: dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176; retrieval url: https://www.ebi.ac.uk/europepmc/webservices/rest/PMC13170886/fullTextXML; method note: Drafted by the collector agent uc-splicing-cnv from the pinned source.; note: Checked by reviewer-scnv against the pinned source; verdict in docs/reviews/use-cases/splicing-cnv-use-cases-2026-10-12.md and in this batch's review.md.
reviewed evaluations: rna-splicing-20261011-fortier2026-eval-riepe-ci-spliceai; rna-splicing-20261011-fortier2026-eval-riepe-legacy-ensemble; rna-splicing-20261011-fortier2026-eval-riepe-openspliceai; rna-splicing-20261011-fortier2026-eval-riepe-spliceai
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