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SpliceAI retrained under the authors' framework (You et al. 2026)

SpliceAI retrained under the authors' framework: Task-specific method retrained on each benchmark training split under the authors' PyTorch framework, with non-PyTorch methods reimplemented in PyTorch; GTEx task input divided into 500 bp blocks; trained and tested three times with different random initialisations.

1 evaluation · 1 result

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Configuration: SpliceAI retrained under the authors' framework (You et al. 2026)Protocol: GTEx tissue-specific splicing prediction, Splice acceptors and donors (You et al. 2026 Supplementary Table 5)
Dataset: GTEx-derived tissue-specific splice site usage dataset (You et al. 2026)		0.8622(0.0000) AUPRC (GTEx splicing task, Splice acceptors and donors, averaged over categories)
fraction · higher

Uncertainty: SD 0.0000

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

SpliceAI on the GTEx splicing task, Splice acceptors and donors

gfm2-20261011-you2026-protocol-gtex-acceptors-donors

Aggregation: Not reported

Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications; You et al. 2026, Supplementary Information · Supplementary Table 5, block 'Splice acceptors and donors', row 'SpliceAI', column 'Average PR-AUC'

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

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Claims, original sources and review scope · Release 2026-10-22-1b7cf027e4f6
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Release 2026-10-22-1b7cf027e4f6 · Record review: source checked

2 source records and release historyDownload this release (gzip)
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Stable ID: gfm2-20261011-you2026-config-spliceai

areas
dna-genomes
contexts
research
method types
specialist
reported name
SpliceAI
foundation model eligible
false
source locator
Methods, 'Construction of tissue-specific alternative splicing prediction task'; Supplementary Tables 4 and 5, row 'SpliceAI'
parameters
Task-specific method retrained on each benchmark training split under the authors' PyTorch framework, with non-PyTorch methods reimplemented in PyTorch (Methods); GTEx task input divided into 500 bp blocks; trained and tested three times with different random initialisations
missing metadata
version: reason: unreported; note: Checkpoint revision not printed; fine-tuning parameters are in Supplementary Table 1
training setting
Retrained from scratch on the task training split
provenance note
SpliceAI retrained under the authors' framework (You et al. 2026), as evaluated in the cited comparison.
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