added warning to readme

[![ISSUES](https://img.shields.io/github/issues/smorabit/scWGCNA)](https://github.com/smorabit/scWGCNA/issues)

**Note:** scWGCNA is under active development, so you will likely run into errors

if you choose to use scWGCNA before its first stable release.

scWGCNA is an R package for performing weighted gene co-expression network analysis [(WGCNA)](https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/) in single-cell

RNA-seq data. scWGCNA constructs co-expression networks in a cell-type-specific manner,

identifies robust modules of inerconnected genes, and provides biological

<div class="page-header"><h1 id="single-cell-co-expression-network-analysis-">single-cell co-expression network analysis <img src="reference/figures/logo.png" align="right" height="20%" width="20%"><a class="anchor" aria-label="anchor" href="#single-cell-co-expression-network-analysis-"></a>

</h1></div>

<p><strong>Note:</strong> scWGCNA is under active development, so you will likely run into errors if you choose to use scWGCNA before its first stable release.</p>

<p>scWGCNA is an R package for performing weighted gene co-expression network analysis <a href="https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/" class="external-link">(WGCNA)</a> in single-cell RNA-seq data. scWGCNA constructs co-expression networks in a cell-type-specific manner, identifies robust modules of inerconnected genes, and provides biological context for these modules. scWGCNA is directly compatible with <a href="https://satijalab.org/seurat/index.html" class="external-link">Seurat</a> objects, one of the most ubiquitous formats for single-cell data. Check out the <a href="articles/basic_tutorial.html">scWGCNA basics tutorial</a> to get started.</p>

<div class="section level2">

<h2 id="installation">Installation<a class="anchor" aria-label="anchor" href="#installation"></a>