A unified computational method for robust identification of differential RNA splicing. Shiba/scShiba can quantify and identify differential splicing events (DSEs) from short-read bulk RNA-seq data and single-cell RNA-seq data. Shiba and scShiba are also implemented as Snakemake workflows, SnakeShiba and SnakeScShiba, respectively.
See CHANGELOG.md for the latest updates.
Shiba comprises four main steps:
- Transcript assembly: Assemble transcripts from RNA-seq reads using StringTie2
- Splicing event identification: Identify alternative mRNA splicing events from assembled transcripts
- Read counting: Count reads mapped to each splicing event using RegTools and featureCounts
- Statistical analysis: Identify DSEs based on Fisher's exact test
A docker image is available at Docker Hub.
docker pull naotokubota/shibaShiba
Shiba -i experiment.tsv -c config.txtSnakeShiba, Snakemake-based workflow of Shiba
snakemake -s SnakeShiba --configfile config.yaml --cores 32 --use-singularityscShiba, a single-cell RNA-seq version of Shiba
scShiba -i experiment.tsv -c config.txtSnakeScShiba, Snakemake-based workflow of scShiba
snakemake -s SnakeScShiba --configfile config.yaml --cores 32 --use-singularitySee the manual document for details.
Kubota N, Chen L, Zheng S. (2024). Shiba: A unified computational method for robust identification of differential RNA splicing across platforms. bioRxiv 2024.05.30.596331