FRASER
FRASER (Find Rare Aberrant Splicing Events in RNA-seq) detects rare aberrant splicing events in transcriptome data using an autoencoder to model read-count expectations and a beta-binomial distribution to score outliers. It supports alternative splicing and intron-retention detection and is optimised for rare disease diagnosis pipelines. Released in Bioconductor 3.23 (v2.8.0).
FRASER — Find Rare Aberrant Splicing Events in RNA-Seq
Version: 2.8.0 (Bioconductor 3.23)
Description: FRASER identifies rare aberrant splicing events in transcriptome profiles by using a deep autoencoder to model expected splicing ratios while correcting for confounding factors, then scoring deviations via a beta-binomial distribution.
- Detection of alternative splicing and intron retention outliers
- Autoencoder-based confounder-aware expectation modelling
- Beta-binomial statistical scoring framework
- Designed for rare disease RNA-seq diagnostic workflows
Biology Domain: Transcriptomics, Rare Disease Genomics, RNA Splicing
Authors: Christian Mertes, Ines Scheller, Vicente Yepez, Julien Gagneur