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scez – single cell, easy mode

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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

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 scez

Then, install scez using uv / pip:

uv pip install scez

Or, to install the latest version from the repository:

uv pip install git+https://github.com/abearab/scez.git

Release files for scez 0.2.1

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Source distribution (sdist)

Source distribution for scez 0.2.1
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Table of built distributions (wheels) for scez 0.2.1
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scez-0.2.1-py3-none-any.whl Python 3 none any Details

Total release size: 18.3 kB

Release files / scez-0.2.1.tar.gz

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0.2.1 This release

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