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Installation

Conda

The following command will create a conda environment named shiba with all dependencies installed.

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conda create -n shiba -c conda-forge -c bioconda shiba

You can also install minimal dependencies for MameShiba, a lightweight version of Shiba . If you want to perform only splicing analysis, this could be a good option. The following command will create a conda environment named mameshiba with minimal dependencies installed.

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conda create -n mameshiba -c conda-forge -c bioconda mameshiba

Docker

We provide a Docker image for Shiba. You can use the following command to pull the latest image from Docker Hub:

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# Pull the latest image
docker pull naotokubota/shiba:v0.6.0

# Login to the container
docker run -it --rm naotokubota/shiba:v0.6.0 bash

# Run Shiba, for example, to see the help message
docker run -it --rm naotokubota/shiba:v0.6.0 shiba.py -h

Memory allocation

You may need to allocate more memory to the container if you are using a large dataset. You can do this in the Docker Desktop settings:

  • Go to Docker Desktop settings
  • Click on the "Resources" tab
  • Increase the memory limit as needed
  • Click "Apply & Restart" to save the changes

Docker Memory Setting

Snakemake

You need to install Snakemake and clone the Shiba GitHub repository on your system:

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# Clone the Shiba repository
git clone https://github.com/Sika-Zheng-Lab/Shiba.git

And please make sure you have Singularity installed on your system as the snakemake workflow uses Singularity to run each step of the pipeline.