sashimi.py 0.1.5

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sashimi.py

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Tutorials

what is sashimi.py

sashimi.py is a tool for visualizing various next-generation sequencing (NGS) data, including DNA-seq, RNA-seq, single-cell RNA-seq and full-length sequencing datasets.

Features of sashimi.py

1. Support various file formats as input
2. Support strand-aware coverage plot
3. Visualize coverage by heatmap, including HiC diagram
4. Visualize protein domain based the given gene id
5. Demultiplex the single-cell RNA/ATAC-seq which used cell barcode into cell population
6. Support visualizing individual full-length reads in read-by-read style
7. Support visualize circRNA sequencing data

Input

sashimi.py supports almost NGS data format, including

• BAM
• Bed
• bigBed
• bigWig
• Depth file generated by samtools depth
• naive Hi-C format

Output

The output will be a pdf and other image file formats which satisfy the requirement of the major journals, and each track on output corresponds these datasets from config file.

Usage

The sashimi.py is written in Python, and user could install it in a variety of ways as follows

Note: if segment fault with multiple processing, please try to use docker image, or just run with -p 1.

1. install from PiPy

   pip install sashimi.py
   

2. install from bioconda

   conda install -c bioconda sashimi-py
   
   # or
   conda env create -n sashimi -f environment.yaml
   
   # or
   conda env create -n sashimi -c conda-forge -c bioconda  -f requirements.txt
   conda activate sashimi && python setup.py install
   

3. using docker image

   docker pull ygidtu/sashimi
   docker run --rm ygidtu/sashimi --help
   
   # or 
   
   git clone from https://github.com/ygidtu/sashimi.py sashimi
   cd sashimi
   docker build -t ygidtu/docker .
   docker run --rm ygidtu/sashimi --help
   

4. install from source code

   git clone https://github.com/ygidtu/sashimi.py sashimi
   cd sashimi
   python setup.py install
   
   sashimipy --help
   # pr
   python main.py --help
   

5. running from a local webserver

    git clone https://github.com/ygidtu/sashimi.py sashimi
    cd sashimi/web
   
    # build the frontend static files
    npm install -g vue-cli vite && npm install
    vite build
   
    # prepare the backend server
    pip install fastapi pydantic jinja2 uvicorn
   
    python server.py --help
   

6. for pipenv users

   git clone https://github.com/ygidtu/sashimi.py
   cd sashimi.py
   pipenv install   # create virtualenv and install required packages
   pipenv shell   # switch to virtualenv
   
   sashimipy --help
   # pr
   python main.py --help
   

Example

python main.py \
  -e chr1:1270656-1284730:+ \
  -r example/example.sorted.gtf.gz \
  --interval example/interval_list.tsv \
  --density example/density_list.tsv \
  --show-side \
  --igv example/igv.tsv \
  --heatmap example/heatmap_list.tsv \
  --focus 1272656-1272656:1275656-1277656 \
  --stroke 1275656-1277656:1277856-1278656@blue \
  --sites 1271656,1271656,1272656 \
  --line example/line_list.tsv \
  -o example/example.png \
  --dpi 300 \
  --width 10 \
  --height 1 \
  --barcode example/barcode_list.tsv \
  --domain --remove-duplicate-umi

here is the output file.

Questions

Visit issues or contact Yiming Zhang and Ran Zhou

Citation

If you use Sashimi.py in your publication, please cite Sashimi.py by

Zhang et al. Sashimi.py: a flexible toolkit for combinatorial analysis of genomic data. bioRxiv 2022.11.02.514803.