GTEx v8 fine-mapped sQTL effect size prediction (SpliceAI2 paper, Spearman)
Rank correlation between model scores and tissue-averaged sQTL effect sizes for 2,385 fine-mapped variants.
Overview
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4 recorded evaluations, 12 metric rows. A comparison chart has not yet been validated for these results. The table retains the individual findings and their sources.
Results
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All evaluations
4 evaluations · 12 results. Different protocols are not a single leaderboard.
Protocol: GTEx v8 fine-mapped sQTL effect size prediction (SpliceAI2 paper, Spearman) · Dataset: GTEx v8 sQTL fine-mapped and null SNVs near junction ends (Jaganathan et al. 2026)
Sorted by Spearman (all variants; essential splice variants excluded) (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 | Spearman (all variants; essential splice variants excluded) | Spearman (exonic variants; essential splice variants excluded) | Spearman (intronic variants; essential splice variants excluded) |
|---|---|---|---|
| SpliceAI2 two-model multispecies ensemble (Jaganathan et al. 2026)Evaluation | 0.73 (best in column) | 0.7 (best in column) | 0.8 (best in column) |
| AlphaGenome raw composite splice score, maximum aggregation (Jaganathan et al. 2026)Evaluation | 0.68 | 0.64 | 0.76 |
| Pangolin, per-position score at the effect position, masking off (Jaganathan et al. 2026)Evaluation | 0.66 | 0.62 | 0.74 |
| SpliceAI 1.3.1, position-resolved delta at the effect position, masking off (Jaganathan et al. 2026)Evaluation | 0.65 | 0.62 | 0.73 |
All 12 result rows with coverage, uncertainty and sources
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Methods and evaluation design
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Baseline coverage
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Protocol coverage CSV (gzip) · Model evaluation matrix (gzip) · Source table (gzip) · Release and checksums (gzip)
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Strengths, limitations and unresolved questions
Evidence
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Evidence table
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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-gtex-sqtl-effect-size
- areas
- dna-genomes
- contexts
- research
- protocol
- Spearman correlation between model score and the sQTL effect size averaged across tissues with a significant association, overall and by exonic or intronic position.
- version
- bioRxiv v1 Extended Data Fig. 2 and Fig. 1d
- metric
- spearman-correlation
- metric direction
- higher
- source locator
- Methods 'Variant effect benchmarks', GTEx sQTL paragraph; Extended Data Fig. 2 panel 'GTEx sQTL (ρ)'
- limitations
- Exon and intron stratum sizes are not printed.; Developer-reported: the SpliceAI2 authors (Illumina) built the benchmark, chose comparator settings and ran every model; AlphaGenome was scored by co-authors at the University of Oxford.; 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 lists GTEx among the recount3 human training sources.; Essential splice variants are excluded, so results do not cover canonical GT/AG disruption.; No confidence intervals or resampling uncertainty are printed.; Preprint (bioRxiv v1), not peer reviewed.
Related records
- uses data: GTEx v8 sQTL fine-mapped and null SNVs near junction ends (Jaganathan et al. 2026)
- assessment: AlphaGenome on GTEx sQTL (spearman-correlation, SpliceAI2 paper)
- assessment: Pangolin on GTEx sQTL (spearman-correlation, SpliceAI2 paper)
- assessment: SpliceAI on GTEx sQTL (spearman-correlation, SpliceAI2 paper)
- assessment: SpliceAI2 on GTEx sQTL (spearman-correlation, SpliceAI2 paper)