rewire.it
model · family

SpliceAI

SpliceAI predicts how sequence variants alter splice-site usage. Its variant annotation tool combines reference sequence with gene annotation.

0 evaluations · 0 metric rows

Shared profile: SpliceAI. This page retains the exact record and its evaluation context.

At a glance

Explanatory profile: source reviewed · Automated source review, 2026-09-16. This does not change the review status of its results.

Inputs, outputs and configuration
PropertyDescription and evidence
InputsVCF, reference FASTA and gene annotationillumina/SpliceAI official source · README.md: package description, License, Usage and Frequently Asked Questions
OutputsAcceptor/donor gain and loss delta scoresillumina/SpliceAI official source · README.md: package description, License, Usage and Frequently Asked Questions
Configuration in this record1.3.1illumina/SpliceAI official source · README.md: package description, License, Usage and Frequently Asked Questions
Model typeNot extracted or verified for this record.
Training dataNot extracted or verified for this record.
Context limitsNot extracted or verified for this record.
AccessNot extracted or verified for this record.
Code licenceNot extracted or verified for this record.
Weights licenceNot extracted or verified for this record.

How it works

Conceptual procedure

Schematic of the documented input, computation and output; not an executable configuration.

Conceptual procedureReference / alternate DNA. Then: Dilated residual convolutions. Then: Acceptor / donor probabilities. Then: Allelic difference. Then: Variant delta scoresReference / alternate DNADilated residual convolutionsAcceptor / donor probabilitiesAllelic differenceVariant delta scores
Read the diagram as text
  1. Reference / alternate DNA
  2. Dilated residual convolutions
  3. Acceptor / donor probabilities
  4. Allelic difference
  5. Variant delta scores
illumina/SpliceAI official source; tkzeng/Pangolin official source · SpliceAI README and linked Jaganathan et al. paper; Pangolin primary paper https://doi.org/10.1186/s13059-022-02664-4, Methods: Deep neural network architecture, direct comparison with SpliceAI

Architecture

SpliceAI uses a residual convolutional network with dilated filters to integrate sequence context. It predicts donor, acceptor and non-splice-site probabilities along the sequence; comparing alleles converts those predictions into variant scores. The output is not tissue-specific.

illumina/SpliceAI official source; tkzeng/Pangolin official source · SpliceAI README and linked Jaganathan et al. paper; Pangolin primary paper https://doi.org/10.1186/s13059-022-02664-4, Methods: Deep neural network architecture, direct comparison with SpliceAI

The tool evaluates reference and alternative alleles and reports predicted acceptor/donor gains and losses with their relative positions. Annotation, search distance and masking determine the reported variant scores.

illumina/SpliceAI official source · README.md: package description, License, Usage and Frequently Asked Questions

Benchmarks and results

Release 2026-09-16-d74d282221a9 · 0 evaluations · 0 metric rows. Different protocols are not a single leaderboard.

No evaluations linked in this release.

Strengths and limitations

Strengths supported by sources

  • Produces splice-specific scores and predicted event positions without fitting a classifier to the user’s assay labels.illumina/SpliceAI official source · README.md: package description, License, Usage and Frequently Asked Questions

Limitations and conditions

  • Code, trained models and precomputed annotations have distinct use terms. Annotation and sequence checks can leave variants unscored.illumina/SpliceAI official source · README.md: package description, License, Usage and Frequently Asked Questions
Profile review details

Primary project documentation or paper inspected for the explanatory claims and cited locations. Reviewed coverage concerns this narrative, not complete metadata, independent reproduction or a performance ranking.

Stable record: catalog-model-spliceai

Sources and history

Release 2026-09-16-d74d282221a9 · Record review: discovered

Download this release
Technical metadata and extraction receipts

Stable ID: catalog-model-spliceai

areas
dna-genomes
method types
specialist
entity level
family
version
1.3.1
reported name
SpliceAI
access
Public archived code under PolyForm Strict; model weights are CC BY-NC 4.0 for non-commercial use.
method type
specialist
missing metadata
checkpoint revision: not_yet_extracted; training data: not_yet_extracted; licence: not_yet_extracted
Related records

Suggest a correction