Command-line tool for the visualization of splicing events across multiple samples
The ggsashimi script can be directly downloaded from this repository:
wget https://raw.githubusercontent.com/guigolab/ggsashimi/master/sashimi-plot.py
Change the execution permissions:
chmod u+x sashimi-plot.py
Provided all dependencies are already installed, you can directly execute the script:
./sashimi-plot.py --help
To download the entire repository, which includes the dockerfile and example files:
git clone https://github.com/guigolab/ggsashimi.git
To avoid dependecies issues, the script is also available through a docker image.
A public ggsashimi Docker image is available in the Docker Hub and can be downloaded as follows:
docker pull guigolab/ggsashimi
Alternatively, we provide the Dockerfile if you want to build your local docker image.
After downloading the repository, move inside the repository folder:
cd ggsashimi
To build the docker image run the following command:
docker build -f docker/Dockerfile -t guigolab/ggsashimi .
This can take several minutes.
Once the image is downloaded or built, to execute ggsashimi with docker:
docker run guigolab/ggsashimi --help
Because the image is used in a docker container which has its own file system, to use the program with local files, a host data volume needs to be mounted.
As an example, you can run this command from the main repository folder:
docker run -w $PWD -v $PWD:$PWD guigolab/ggsashimi -b examples/input_bams.tsv -c chr10:27040584-27048100
The '-w' option sets the working directory inside the container to the current directory. The '-v' option mounts the current working directory and all child folders inside the container to the same path (host_path:container_path). If your files are in another folder, for example the annotation file is stored in a different folder then the one containing the bam file, you can mount extra folders like this:
f="$DIR/annotation.gtf"
docker run -w $PWD -v $PWD:$PWD -v $DIR:$DIR guigolab/ggsashimi -b examples/input_bams.tsv -c chr10:27040584-27048100 -g $f
You can even mount a single file:
docker run -w $PWD -v $PWD:$PWD -v $f:$f guigolab/ggsashimi -b examples/input_bams.tsv -c chr10:27040584-27048100 -g $f
Execute the script with --help option for a complete list of options.