RNA-seq confirmation of SpliceAI2-prioritised rare variants in panel genes, Genomics England rare-disease participants (SpliceAI2 paper)
Count how many rare variants prioritised by SpliceAI2 (> 0.25) in phenotype-matched panel genes show the predicted splicing change in the participant's RNA-seq.
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1 recorded evaluation, 2 metric rows. A comparison chart has not yet been validated for these results. The table retains the individual findings and their sources.
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Protocol: RNA-seq confirmation of SpliceAI2-prioritised rare variants in panel genes, Genomics England rare-disease participants (SpliceAI2 paper) · Dataset: Genomics England rare-disease participants with WGS and blood RNA-seq (Jaganathan et al. 2026)
Sorted by True positives (of the 23 prioritised variants, those showing RNA-seq evidence of the predicted splicing change) (higher is better). The best value in each column is highlighted. Decimals are rounded for display; each value links to the printed value and its source.
| Tested configuration | True positives (of the 23 prioritised variants, those showing RNA-seq evidence of the predicted splicing change) | Count (rare variants prioritised at SpliceAI2 > 0.25 in panel genes) |
|---|---|---|
| SpliceAI2 two-model multispecies ensemble (Jaganathan et al. 2026)Evaluation | 17 | 23 |
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Evidence
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Sources and history
Release 2026-10-22-1b7cf027e4f6 · Record review: source checked
1 source record and release history
- A unified framework for quantitative splicing and transcript prediction (Jaganathan et al., bioRxiv 2026) · Original source · bioRxiv preprint version 1, posted 2026-10-11; full-text PDF (57 pages)
Technical metadata and extraction receipts
Stable ID: rna-splicing-20261013-spliceai2-protocol-gel-prioritised-confirmation
- areas
- dna-genomes; rna-transcriptomes
- contexts
- clinical_research
- protocol
- Participants with RNA-seq and monoallelic disorders, panels of up to 500 genes; rare variants with SpliceAI2 > 0.25 in panel genes are prioritised and checked in RNA-seq against 20 pooled controls lacking the variant (sashimi plots, Extended Data Fig. 5).
- version
- bioRxiv v1 Main text and Extended Data Fig. 5
- metric
- count
- metric direction
- unknown
- unit
- count
- source locator
- Main 'Contribution to rare genetic disease' paragraph 4; Fig. 4h,i; Extended Data Fig. 5
- limitations
- SpliceAI2 only: no comparator model was put through the same prioritisation and confirmation.; The confirmation criterion for these 23 variants is described through sashimi plots against pooled controls; a numeric rule is not stated for this step.; Confirmation of a splicing change is not a diagnosis or a pathogenicity classification.; Developer-reported: the SpliceAI2 authors (Illumina) built the benchmark and ran SpliceAI2; no other model is scored on it.; Training overlap: SpliceAI2 was trained on all human genes except those on chromosomes 21 and 22, and the benchmark is genome-wide, so most variants lie in genes seen in training. Supplementary Table 1 does not list Genomics England data among the training sources.; No confidence intervals or resampling uncertainty are printed.; Preprint (bioRxiv v1), not peer reviewed.