ygidtu/trackplot repository overview

⁠trackplot

Tutorials⁠

⁠what is trackplot

trackplot 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 trackplot

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

trackplot supports almost NGS data format, including

• BAM
• Bed
• Depth file generated by samtools depth
• bigBed [pyBigWig⁠ optional]
• bigWig [pyBigWig⁠ optional]
• naive Hi-C format [hicmatrix⁠ optional]

⁠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 trackplot is written in Python, and user could install it in a variety of ways as follows

⁠Notes

1. install from PyPi

   # optional, enable bigWig, bigBed and hicMatrix support
   pip install pybigwig hicmatrix
   
   pip install trackplot
   # __Note:__ We noticed some pypi mirrors are not syncing some packages we depend on,
   # therefore please try another pypi mirror once you encounter
   # `No local packages or working download links found for xxx`
   

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2. using docker image

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

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3. install from source code

   git clone https://github.com/ygidtu/trackplot trackplot
   cd trackplot
   pip install -r requirements.txt
   python setup.py install
   
   # optional, enable bigWig, bigBed and hicMatrix support
   pip install pybigwig hicmatrix
   
   trackplot --help
   # or
   python main.py --help
   

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4. install from bioconda

   conda install -c bioconda -c conda-forge trackplot
   
   # or install trackplot into an isolated environments
   conda create -n trackplot -c bioconda -c conda-forge trackplot
   
   # or install latest trackplot
   git clone https://github.com/ygidtu/trackplot.git trackplot
   cd trackplot
   conda create -n trackplot -f environment.yaml
   

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5. for pipenv or poetry users

   git clone https://github.com/ygidtu/trackplot
   cd trackplot
   
   # pipenv
   # create virtualenv and install required packages
   pipenv install
   # optional, with `--pypi-mirror https://pypi.tuna.tsinghua.edu.cn/simple` to specify your faverate PyPi mirror
   # optional, with `--skip-lock` once encounter locking issues
   
   # switch to virtualenv
   pipenv shell && python main.py --help
   
   # or just run with pipenv
   pipenv run python main.py --help
   
   
   # poetry
   # once facing installation issues, please try to change PyPi mirror in tool.poetry.source section of pyproject.toml
   # create virtualenv and install required packages
   poetry install
   
   # switch to virtualenv
   poetry shell  && python main.py --help
   
   # or just run with poetry
   poetry run python main.py --help
   

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6. running from a local webserver

   Install trackplot before set up the web server

   git clone https://github.com/ygidtu/trackplot trackplot
   cd trackplot/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
   

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⁠Example

The example folder is downloaded from here.⁠ And a more detailed tutorial could be found at here.⁠

python main.py \
  -e chr1:1270656-1284730:+ \
  -r example/example.sorted.gtf.gz \
  --interval example/interval_list.tsv \
  --density example/density_list.tsv \
  --show-site \
  --show-junction-num \
  --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.png \
  --dpi 300 \
  --width 10 \
  --height 1 \
  --barcode example/barcode_list.tsv \
  --domain --remove-duplicate-umi \
  --normalize-format cpm \
  -p 4

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. bioRxiv, 2022.11.02.514803.⁠