Single Cell Analysis, Easy Mode!
Project description
scez – single cell, easy mode
Description
There are many tools available for single-cell RNA-seq analysis, but they often require a lot of understanding of the underlying algorithms, reading of documentation, and setting up analysis environments. This takes time and effort, and can be a barrier to entry for many projects. Single-Cell Best Practices is a great resource for learning about the best practices for single-cell analysis. scez
aims to provide functionalities for single-cell analysis through definitions of analysis "tasks" and implementation of these "best practices" in a user-friendly way.
This is more a personal effort to streamline my own analysis workflows, but I hope it can be useful to others as well.
Installation
Make sure you have mamba installed in your base environment. If not, install it with:
conda install mamba -n base -c conda-forge
Then, create a new conda environment with the provided environment.yml
file and activate it. This will install all necessary dependencies for scez.
conda env create -f https://raw.githubusercontent.com/abearab/scez/main/environment.yml
conda activate scez
Finally, install scez with:
pip install scez
Or, if you want to install the latest version from the repository:
pip install git+https://github.com/abearab/scez.git
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