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<!DOCTYPE html>
<html class="no-js" lang="en">
<head>
<meta charset="utf-8">
<title>SCCAF</title>
<meta name="author" content="Chichau Miau">
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<meta property="og:description" content="The quantitative assessment of the clustering of single cell data is a critical problem to be solved in data analysis. We present a machine learning based self-projection framework(SCCAF) to assess …">
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<meta itemprop="name" content="SCCAF" />
<meta itemprop="description" content="The quantitative assessment of the clustering of single cell data is a critical problem to be solved in data analysis. We present a machine learning based self-projection framework(SCCAF) to assess the clustering quality of single-cell RNA-seq data, find similar cell clusters that encode identical signature, detect potential doublets and find marker genes. On both simulated and real scRNA-Seq datasets, we illustrate the capabilities of SCCAF. We show that SCCAF greatly helps in finding encodable cell clusters and may useful contribute to the building of standard operating procedure of high-throughput single-cell sequencing data." />
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<section class="page-header">
<h1 class="project-name">SCCAF</h1>
<h2 class="project-tagline">Single-Cell Clustering Assessment Framework</h2>
</section>
<h2 id="description">Description</h2>
<p>The quantitative assessment of the clustering of single cell data is a critical problem to be solved in data analysis. We present a machine learning based self-projection framework(SCCAF) to assess the clustering quality of single-cell RNA-seq data, find similar cell clusters that encode identical signature, detect potential doublets and find marker genes. On both simulated and real scRNA-Seq datasets, we illustrate the capabilities of SCCAF. We show that SCCAF greatly helps in finding encodable cell clusters and may useful contribute to the building of standard operating procedure of high-throughput single-cell sequencing data.</p>
<h2 id="installation">Installation</h2>
<ul>
<li>
<p>download SCCAF package
<code class="highlighter-rouge">git clone https://github.com/SCCAF/sccaf.git</code></p>
</li>
<li>
<p>go into the directory:
<code class="highlighter-rouge">cd sccaf</code></p>
</li>
<li>
<p>install
<code class="highlighter-rouge">python setup.py install</code></p>
</li>
</ul>
<h2 id="usage">Usage</h2>
<p>Please refer to <a href="https://github.com/SCCAF/sccaf_example">sccaf_example</a> for detailed usage of the program.</p>
<h2 id="citation">Citation</h2>
<p>Please cite: Zhichao Miao, Alvis Brazma, Sarah Teichmann 2018 Single cell RNA-seq data helps machine learning in finding encodeable cell clusters.</p>
<h2 id="support-or-contact">Support or Contact</h2>
<p>If you have any problem with SCCAF, please contact <a href="mailto:zmiao@ebi.ac.uk">Chichau</a> for help.</p>
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<h1>SCCAF</h1>
<p>Single-Cell Clustering Assessment Framework</p>
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