Use Pangolin RNA Splicing Prediction

Official Neurosnap webserver for accessing Pangolin RNA Splicing Prediction online.

BETA Multi-omics Genomics

Overview

Pangolin is a deep learning model that predicts RNA splicing from DNA sequence with high accuracy. It outperforms state-of-the-art methods in predicting splice site strength across multiple tissues (heart, liver, brain, and testis). By training on data from four species (human, rhesus macaque, rat, and mouse), Pangolin effectively predicts the impact of common, rare, and lineage-specific genetic variants on RNA splicing. It shows remarkable potential for identifying pathogenic, loss-of-function mutations, especially those that are not missense or nonsense, making it a valuable tool for interpreting disease-causing variants.

Neurosnap Overview

The Pangolin RNA Splicing Prediction online webserver allows anybody with a Neurosnap account to run and access Pangolin RNA Splicing Prediction, no downloads required. Information submitted through this webserver is kept confidential and never sold to third parties as detailed by our strong terms of service and privacy policy.

View Paper

Features

  • Predicts splice site probability and usage for four organs: heart, liver, brain, and testis.
  • Trained on sequence and RNA splicing data from four different species: human, rhesus macaque, mouse, and rat.
  • Outperforms existing methods like SpliceAI, MMSplice, and HAL on splice site prediction.
  • Accurately predicts the effects of rare and common genetic variants on RNA splicing.
  • Identifies loss-of-function (LOF) mutations with high precision and recall, aiding in the identification of pathogenic variants.
  • Models epistatic effects, enabling accurate prediction for combinations of genetic variants.

Statistics

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API Request

Access Pangolin RNA Splicing Prediction using the Neurosnap API by sending a request using any programming language with HTTP support. To safely generate an API key, visit the API tab of your overview page.

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Job Note

Provide a name or description for your job to help you organize and track its results. This input is solely for organizational purposes and does not impact the outcome of the job.

Configuration & Options

Service Inputs

Choose the genome assembly version for your variant coordinates.

Number of bases on either side of the variant to score for splicing changes.

Reduces false positives by ignoring splice gains at known sites and splice losses at new sites.

Variant Input Format

Each row should define one genetic variant with four comma-separated values:

CHROM,POS,REF,ALT
  • CHROM → The chromosome, must be in the format ‘chr’ followed by a number (1-22) (e.g., chr1, chr2).
  • POS → The position, must be a positive integer.
  • REF → The reference allele, must only contain A, C, G, T.
  • ALT → The alternate allele, must only contain A, C, G, T.


🔹 Example Input:

chr1,123456,A,T
chrX,789101,C,G

Specify genetic variants. See above instructions for more details.

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