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MBNL1-associated junction usage differences across myotonic dystrophy severity groups, held-out genes (SpliceAI2 paper, Pearson)

Pearson correlation between predicted and observed junction usage differences between healthy and three disease-severity groups.

1 evaluation · 1 result

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Tested configurationProtocol and datasetFindingEvidence and details
Configuration: SpliceAI2 fine-tuned on myotonic dystrophy type 1 muscle RNA-seq (Jaganathan et al. 2026)Protocol: MBNL1-associated junction usage differences across myotonic dystrophy severity groups, held-out genes (SpliceAI2 paper, Pearson)
Dataset: Myotonic dystrophy type 1 tibialis anterior RNA-seq, GEO GSE86356 (as used by Jaganathan et al. 2026)
0.26 Pearson (mean over disease-severity condition pairs; held-out genes)
unitless · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

SpliceAI2 myotonic dystrophy fine-tune on MBNL1-associated junction usage differences

rna-splicing-20261013-spliceai2-protocol-dm1-mbnl1

Aggregation: Not reported

A unified framework for quantitative splicing and transcript prediction (Jaganathan et al., bioRxiv 2026) · Main 'Modeling tissue-specific splicing' paragraph 4 '(mean Pearson r = 0.26)'

Source checking is not independent reproduction. Release 2026-10-22-1b7cf027e4f6.

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Technical metadata and extraction receipts

Stable ID: rna-splicing-20261013-spliceai2-protocol-dm1-mbnl1

areas
rna-transcriptomes
contexts
research
protocol
For each condition pair, junctions with more than 500 anchor reads and absolute measured logit difference above 0.01; usage clipped at 1e-4 before logit; Pearson per pair, mean over pairs reported in the text.
version
bioRxiv v1 Main text and Fig. 2e
metric
pearson-correlation
metric direction
higher
source locator
Methods 'MBNL1-depleted myotonic dystrophy'; Fig. 2e
limitations
SpliceAI2 only; per-pair values are a heatmap without printed numbers.; Developer-reported: the SpliceAI2 authors (Illumina) built the benchmark and ran SpliceAI2; no other model is scored on it.; Training overlap: results are reported for 'held-out genes', which the paper does not define for this fine-tune; the pretrained encoder saw all human genes except those on chromosomes 21 and 22.; No confidence intervals or resampling uncertainty are printed.; Preprint (bioRxiv v1), not peer reviewed.
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