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.
First, create a new conda environment with the provided environment.yml file:
conda env create -f https://raw.githubusercontent.com/abearab/scez/main/environment.yml
conda activate scezThen, install scez using uv / pip:
uv pip install scezOr, to install the latest version from the repository:
uv pip install git+https://github.com/abearab/scez.git