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SCANet: A workflow for single-cell co-expression based analysis

SCANet, a new python package that incorporates the inference of gene co-expression networks from single-cell gene expression data and a complete analysis of the identified modules through trait and cell type associations, hub genes detection, deciphering of co-regulatory signals in co-expression, and drug-gene interactions identification. This will likely accelerate network analysis pipelines and advance systems biology research.

Installation

To install SCANet.

pip install scanet

Finally, it should be possible to import drugstone to your python script.

import scanet

You can use

import scanet as sn

SCANet officially supports Python 3.6+.

Usage

A full detailed example of SCANet : Refer to this Jupyter Notebook.

In this Jupyter Notebook, we explored all aspects of gene coexpression networks (GCNs) using SCANet through a full analysis of the 3k PBMCs from 10x Genomics.

Metadata

Release files for scanet 0.1.11

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Total release size: 23.3 MB

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