trackplot 0.3.2

The 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. https://sashimi.readthedocs.io/

trackplot

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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 Python3 (python_requires='>=3.8'), and user could install it in a variety of ways as follows

Notes

1. For microsoft windows, mac (apple silicon) and other arm platform users, due to pysam, pybigwig and hicmatrix do not support those platforms, trackplot couldn't be installed by pypi or conda, pleas use docker image as alternative
2. if segment fault with multiple processing, please try to use docker image, or just run with -p 1.
3. if Please install pyBigWig and hicmatrix occurs, please check the official document of pyBigWig and hicmatrix to solve their requirements.

Using trackplot by a command line

1. install from PyPi

Before running this command line, please check python (>=3.8) was installed.

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. AppImage (Linux/WSL x86_64 platform only)

All the AppImage files were tested on the official pre-built GNU/Linux distributions docker images:

• Arch: appimagecrafters/tests-env:archlinux-latest
• Fedora: appimagecrafters/tests-env:fedora-30
• Debian: appimagecrafters/tests-env:debian-stable
• Ubuntu: appimagecrafters/tests-env:ubuntu-bionic
• Centos: appimagecrafters/tests-env:centos-7

Due to the limitation of AppImage technic itself, we only provide AppImage for Linux and Windows subsystem for Linux (x86_64 platform) users. Once you have installation issues and not familiar with docker, please download the AppImage file from our releases.

Once the AppImage file couldn't work properly please open an issue in this repo, and provide us the system platform and full error messages for us to debug.

Notes:

1. the AppImage will decompress all bundled files before execution, therefore it will a little bit slower than command line tools and source code
2. please use absolute path instead of relative path.

# example with version v0.3.2, please using your interested version according to your needs
export VERSION=0.3.2
chmod +x trackplot-${VERSION}-x86_64.AppImage
./trackplot-${VERSION}-x86_64.AppImage --help

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3. using docker image

Known issue: the logging time may have several hours mismatch with your local time, due to timezone settings inner the image.

docker pull ygidtu/trackplot
docker run --rm ygidtu/trackplot --help

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4. install from bioconda

First make sure your conda is properly installed.

# Check if conda has been successfully installed.
conda --version

# if conda is not installed, refer to https://conda.io/projects/conda/en/latest/user-guide/install/download.html

After successful installation

# install trackplot into the default conda env 
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

# activate the trackplot environment and execute the command line tool
conda activate trackplot
trackplot --help

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For additional installation information please visit here.

Using trackplot by a local webserver

1. AppImage (Linux/WSL x86_64 only)

# example with version v0.3.2, please using your interested version according to your needs
export VERSION=0.3.2
gunzip trackplot-${VERSION}-x86_64.AppImage
chmod +x trackplot-${VERSION}-x86_64.AppImage
./trackplot-${VERSION}-x86_64.AppImage --help

# startup webserver
./trackplot-${VERSION}-x86_64.AppImage --start-server --host 127.0.0.1 --port 5000 --plots ./plots

Note: the --plots were required while using appimages

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2. Running using command line

trackplot --start-server --host 127.0.0.1 --port 5000 --plots ./plots

3. Running using docker image

docker pull ygidtu/trackplot

# Deploy the server
docker run --name trackplot \
  --rm -v $PWD/example:/data -v $PWD/plots/:/plots -p 5000:5000 ygidtu/trackplot \
  --start-server \
  --host 0.0.0.0 \
  --data /data \
  --plots /plots

-p: public and private port for the server, default:5000(public):5000(private)

• -v, --volume: mount the working directory to docker container, for example, the $PWD/data could replace by the path to your directory contains all necessary data
• --user: prevent docker read and write file using root privileges
• the rest usage please check Command line usage

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Example

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

# example of basic plot types
python ../main.py \
  -e chr1:1270656-1284730:+ \
  -r example/example.sorted.gtf.gz \
  --interval example/interval_list.tsv \
  --density example/density_list.tsv \
  --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 \
  --annotation-scale .3 \
  -p 4

if trackplot was installed by docker, here is the cmd

## The absolute path is required in Docker env.
 
cat $PWD/example/interval_list.tsv |grep -v '^#' | while read line; do echo $PWD/${line}; done > $PWD/example/interval_list.abspath.tsv
cat $PWD/example/density_list.tsv |grep -v '^#' | while read line; do echo $PWD/${line}; done > $PWD/example/density_list.abspath.tsv
cat $PWD/example/igv.tsv |grep -v '^#' | while read line; do echo $PWD/${line}; done > $PWD/example/igv.abspath.tsv
cat $PWD/example/heatmap_list.tsv |grep -v '^#' | while read line; do echo $PWD/${line}; done > $PWD/example/heatmap_list.abspath.tsv

docker run -v $PWD:$PWD --rm ygidtu/trackplot \
  -e chr1:1270656-1284730:+ \
  -r $PWD/example/example.sorted.gtf.gz \
  --interval $PWD/example/interval_list.tsv \
  --density $PWD/example/density_list.tsv \
  --show-junction-num \
  --igv $PWD/example/igv.tsv \
  --heatmap $PWD/example/heatmap_list.tsv \
  --focus 1272656-1272656:1275656-1277656 \
  --stroke 1275656-1277656:1277856-1278656@blue \
  --sites 1271656,1271656,1272656 \
  --line $PWD/example/line_list.tsv \
  -o example.png \
  --dpi 300 \
  --width 10 \
  --height 1 \
  --barcode $PWD/example/barcode_list.tsv \
  --domain --remove-duplicate-umi \
  --normalize-format cpm \
  --annotation-scale .3 \
  -p 4

here is the output file.

Questions

Visit issues or contact Yiming Zhang or Ran Zhou

Citation

If you use the tool in your publication, please cite by

Zhang et al. bioRxiv, 2022.11.02.514803.