biagii/magic repository overview

⁠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: [email protected]⁠