Shiba (v0.8.2)

A versatile computational method for systematic identification of differential RNA splicing. Shiba/scShiba can quantify and identify differential splicing events (DSEs) from 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.

Important

Shiba now supports long-read RNA-seq data analysis! Please check the manual for more details.

Overview

Shiba comprises four main steps:

1. Transcript assembly: Assemble transcripts from RNA-seq reads using StringTie
2. Splicing event identification: Identify alternative mRNA splicing events from assembled transcripts
3. Read counting: Count reads mapped to each splicing event using RegTools and featureCounts
4. Statistical analysis: Identify DSEs based on Fisher's exact test

Installation

Conda

conda create -n shiba -c conda-forge -c bioconda shiba
conda activate shiba
pip install styleframe==4.2 # optional, for generating outputs in Excel format.

If you want to perform only splicing analysis, you can install minimal dependencies and run MameShiba, a lightweight version of Shiba.

conda create -n mameshiba -c conda-forge -c bioconda mameshiba

Docker

docker pull naotokubota/shiba:v0.8.2

Usage

Manual for Shiba is available at https://sika-zheng-lab.github.io/Shiba/.

Shiba

shiba.py -p 4 config.yaml

MameShiba, a lightweight version of Shiba

shiba.py --mame -p 4 config.yaml

SnakeShiba, Snakemake-based workflow of Shiba

snakemake -s snakeshiba.smk --configfile config.yaml --cores 4 --use-singularity

scShiba, a single-cell RNA-seq version of Shiba

scshiba.py -p 4 config.yaml

SnakeScShiba, Snakemake-based workflow of scShiba

snakemake -s snakescshiba.smk --configfile config.yaml --cores 4 --use-singularity

Visualization

Do you want to visualize the results of Shiba analysis? Try 🐕 shiba2sashimi 🍣 !

Contributing

Thank you for wanting to improve Shiba! If you have any bugs or questions, feel free to open an issue or pull request.

Citation

Kubota N, Chen L, Zheng S. Shiba: a versatile computational method for systematic identification of differential RNA splicing across platforms. Nucleic Acids Research 53(4), 2025, gkaf098.

Authors

• Naoto Kubota (0000-0003-0612-2300)
• Liang Chen (0000-0001-6164-4553)
• Sika Zheng (0000-0002-0573-4981)