🐕 shiba2sashimi 🍣 (v0.1.7)
A utility to create Sashimi plots, a publication-quality visualization of RNA-seq data, from Shiba output. Greatly inspired by rmats2sashimiplot and MISO's original implementation.
Quick start
shiba2sashimi -e /path/to/Shiba/experiment_table.tsv \
-s /path/to/Shiba/workdir/ -o img/sashimi_example.png \
--id "SE@chr2@157561213-157561293@157560260-157561542"
How to install
pip
pip install shiba2sashimi
or
git clone https://github.com/Sika-Zheng-Lab/shiba2sashimi.git
cd shiba2sashimi
pip install .
conda
conda create -n shiba2sashimi -c bioconda -c conda-forge shiba2sashimi
conda activate shiba2sashimi
Docker
docker pull naotokubota/shiba2sashimi
Dependencies
- python (>=3.9)
- numpy (>=1.18.0,<2.0.0)
- matplotlib (>=3.1.0)
- pysam (>=0.22.0)
Usage
usage: shiba2sashimi [-h] -e EXPERIMENT -s SHIBA -o OUTPUT [--id ID] [-c COORDINATE] [--samples SAMPLES] [--groups GROUPS] [--colors COLORS] [--width WIDTH] [--extend_up EXTEND_UP] [--extend_down EXTEND_DOWN]
[--smoothing_window_size SMOOTHING_WINDOW_SIZE] [--font_family FONT_FAMILY] [--nolabel] [--nojunc] [--minimum_junc_reads MINIMUM_JUNC_READS] [--dpi DPI] [-v]
shiba2sashimi v0.1.7 - Create Sashimi plot from Shiba output
optional arguments:
-h, --help show this help message and exit
-e EXPERIMENT, --experiment EXPERIMENT
Experiment table used for Shiba
-s SHIBA, --shiba SHIBA
Shiba working directory
-o OUTPUT, --output OUTPUT
Output file
--id ID Positional ID (pos_id) of the event to plot
-c COORDINATE, --coordinate COORDINATE
Coordinates of the region to plot
--samples SAMPLES Samples to plot. e.g. sample1,sample2,sample3 Default: all samples in the experiment table
--groups GROUPS Groups to plot. e.g. group1,group2,group3 Default: all groups in the experiment table. Overrides --samples
--colors COLORS Colors for each group. e.g. red,orange,blue
--width WIDTH Width of the output figure. Default: 8
--extend_up EXTEND_UP
Extend the plot upstream. Only used when not providing coordinates. Default: 500
--extend_down EXTEND_DOWN
Extend the plot downstream. Only used when not providing coordinates. Default: 500
--smoothing_window_size SMOOTHING_WINDOW_SIZE
Window size for median filter to smooth coverage plot. Greater value gives smoother plot. Default: 21
--font_family FONT_FAMILY
Font family for labels
--nolabel Do not add sample labels and PSI values to the plot
--nojunc Do not plot junction arcs and junction read counts to the plot
--minimum_junc_reads MINIMUM_JUNC_READS
Minimum number of reads to plot a junction arc. Default: 1
--dpi DPI DPI of the output figure. Default: 300
-v, --verbose Increase verbosity
Contributing
Thank you for wanting to improve shiba2sashimi! If you have any bugs or questions, feel free to open an issue or pull request.
Citation
If you use shiba2sashimi in your research, please cite the original Shiba paper:
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)
Metadata
Release files for shiba2sashimi 0.1.7
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| shiba2sashimi-0.1.7-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 29.0 kB
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