cbiagii / MAGIC

Docker image for MAGIC (Markov Affinity-based Graph Imputation of Cells)

Docker image for MAGIC (Markov Affinity-based Graph Imputation of Cells)

Markov Affinity-based Graph Imputation of Cells (MAGIC) is an algorithm for denoising high-dimensional data most commonly applied to single-cell RNA sequencing data. MAGIC learns the manifold data, using the resultant graph to smooth the features and restore the structure of the data. The software is available on https://github.com/KrishnaswamyLab/MAGIC

Docker installation

To install docker follow the instructions in the links below depending on your operating system:

• CentOS: https://docs.docker.com/install/linux/docker-ce/centos/
• Debian: https://docs.docker.com/install/linux/docker-ce/debian/
• Fedora: https://docs.docker.com/install/linux/docker-ce/fedora/
• Ubuntu: https://docs.docker.com/install/linux/docker-ce/ubuntu/
• MacOS: https://docs.docker.com/docker-for-mac/install/
• Windows: https://docs.docker.com/docker-for-windows/install/

Pulling Docker Image

Once docker is installed, the next step is to pull the scmatch image from dockerhub using the following command:

docker pull biagii/magic

Running image

docker run -it --rm --name [ANY_NAME] -v /server/path/:/docker/path biagii/magic python

Help

This docker image is based on MAGIC tool developed by David van Dijk. Any doubt about how to use the parameters of the tool can be found in https://github.com/KrishnaswamyLab/MAGIC and further details in the original paper.

Any questions in Docker image contact the developer by email: [e-mail]