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<title>muon</title>
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<div id="summary_title">
<h1>muon</h1>
</div>
<div id="summary_subtitle">
<h2>multimodal omics<br>Python framework</h2>
</div>
</div>
</div>
<!-- <div id="summary_text">
<h1>muon</h1>
<h2>multimodal omics<br>Python framework</h2>
</div> -->
<div class="action_buttons">
<a href="#install" class="action_button"><span class="action_link">pip install muon</span></a>
<a href="https://muon.readthedocs.io/en/latest/index.html" target="_blank" class="git"><span class="git_link">docs</span></a>
<a href="https://muon-tutorials.readthedocs.io/en/latest/index.html" target="_blank" class="git"><span class="git_link">tutorials</span></a>
<a href="https://github.com/scverse/muon" target="_blank" class="git"><span class="git_link">github</span></a>
<!-- <a href="#start" class="action_button"><span class="action_link">learn more</span></a> -->
<!--, <a href="https://biorxiv.org" target="_blank" class="ppr">Paper</a>, -->
<!--<a href="https://twitter.com/gtcaa/" target="_blank" class="twt">Twitter thread</a>-->
</div>
</div>
</div>
<div id="content">
<div class="content_page">
<div id="start">
<p><span class="muon">muon</span> is a Python framework designed to work with multimodal omics data. Incentified by recent advances in acquisition of multimodal data from individual cells, <span class="muon">muon</span> aims to provide convenience and speed to its users enabling standardised analysis while staying flexible and expandable. <span class="muon">muon</span> stands on the shoulders of and integrates with <a href="https://github.com/theislab/anndata" target="_blank">annotated data</a> object specification and <a href="https://github.com/theislab/scanpy" target="_blank">scanpy</a> library for single-cell analysis in Python.</p>
</div>
</div>
<div id="showcase">
<div class="showcase_element">
<a href="https://github.com/scverse/muon-tutorials/tree/master/single-cell-rna-atac/pbmc10k" target="_blank"><span class="clickable"></span></a>
<h4>Application highlight</h4>Analysis of single‑cell <span class="highlight">RNA & ATAC</span> data from peripheral blood mononuclear cells</div>
<div class="showcase_element showcase_element">
<!-- <a href="https://www.nature.com/articles/nmeth.4380" target="_blank"><span class="clickable"></span></a>
<h4>Potential application</h4>Analysis of single‑cell <span class="highlight">RNA & surface protein</span> measurements from cord blood mononuclear cells -->
<a href="https://github.com/scverse/muon-tutorials/tree/master/cite-seq/" target="_blank"><span class="clickable"></span></a>
<h4>Application highlight</h4>Analysis of single‑cell <span class="highlight">RNA & surface protein</span> measurements from peripheral blood mononuclear cells
</div>
<div class="showcase_element showcase_element_tbd">
<a href="https://elifesciences.org/articles/63632" target="_blank"><span class="clickable"></span></a>
<h4>Potential application</h4>Analysis of trimodal single‑cell data – <span class="highlight">RNA, ATAC, epitopes</span> – from peripheral blood mononuclear cells
</div>
<div class="showcase_element showcase_element_tbd">
<a href="https://www.nature.com/articles/s41467-018-03149-4" target="_blank"><span class="clickable"></span></a>
<h4>Potential application</h4>Analysis of single‑cell <span class="highlight">scNMT-seq</span> data
</div>
<div class="showcase_element showcase_element_tbd">
<a href="https://www.cell.com/cell/pdf/S0092-8674(20)30809-6.pdf" target="_blank"><span class="clickable"></span></a>
<h4>Potential application</h4>Analysis of single‑cell <span class="highlight">RNA & intracellular protein activity</span> from peripheral blood mononuclear cells
</div>
<div class="showcase_element showcase_element_tbd">
<a href="https://science.sciencemag.org/content/367/6476/eaay1645" target="_blank"><span class="clickable"></span></a>
<h4>Potential application</h4>Analysis of <span class="highlight">RNA & ATAC</span> data from human stem cell‑derived 3D forebrain organoids
</div>
</div>
<div class="content_page">
<div id="concept">
<img id="cell_render" src="cell_render.png"/>
<!-- <img id="cube_render" src="cube_render.png"/> -->
</div>
</div>
<div class="content_page">
<h1>get to know muon</h1>
<h2 class="h2_first">multimodal data containers</h2>
<div class="content_block">
<div class="content_img" id="img_mudata">
<img src="img/mudata.png"/>
</div>
<div class="content_text">
<div>
<p><span class="muon">muon</span> introduces <b>multimodal data containers</b> allowing Python users to work with increasigly complex datasets efficiently and to build new workflows and computational tools around it</p>
</div>
<code>
<span class="code_header">~> python<br></span>
mdata<br>
| MuData object with n_obs × n_vars = 10110 × 110101<br>
|  2 modalities<br>
|   atac: 10110 x 100001<br>
|   rna: 10110 x 10100<br>
</code>
<div class="content_text_br"></div>
</div>
</div>
<div class="content_block">
<div class="content_img" id="img_multimodal">
<img src="img/multimodal.png"/>
</div>
<div class="content_text">
<h2>multi-omics methods</h2>
<div>
<p><span class="muon">muon</span> brings <b>multi-omics methods</b> availability to a whole new level: state-of-the-art methods for multi-omics data integration are just a function call away</p>
</div>
<code>
<span class="code_header"># multi-omics factor analysis<br></span>
mu.tl.mofa(mdata)
</code>
<code>
<span class="code_header"># weighted nearest neighbours<br></span>
mu.pp.neighbors(mdata)
</code>
<div class="content_text_br"></div>
</div>
</div>
<div class="content_block">
<div class="content_img" id="img_unimodal">
<img src="img/unimodal.png"/>
</div>
<div class="content_text">
<h2>methods crafted for omics</h2>
<div>
<p><span class="muon">muon</span> features methods for specific <b>omics</b> such as ATAC-seq and CITE-seq making it an extendable solution and allowing for prospective growth in an open-source environment</p>
</div>
<code>
<span class="code_header"># TF-IDF transformation<br></span>
ac.pp.tfidf(mdata.mod['atac'])
</code>
<code>
<span class="code_header"># denoising and scaling by background<br></span>
pt.pp.dsb(mdata.mod['prot'])
</code>
<div class="content_text_br"></div>
</div>
</div>
</div>
<div id="install" class="content_page">
<h1>Get muon</h1>
<code>
<span class="code_header">❯ </span>
pip install muon
<span class="code_header"><br> # or<br></span>
<span class="code_header">❯ </span>
pip install git+https://github.com/scverse/muon
</code>
<br/><br/><br/><br/>
<h1>Get started</h1>
<code>
<span class="code_header">~> python<br></span>
import muon as mu
</code>
<div>
<p><a href="https://muon.readthedocs.io/en/latest/io/input.html" target="_blank">Load data easily</a> whether you start from raw count matrices, Loom files or AnnData objects. Or Snap files. Or Seurat objects. Or MultiAssayExperiment objects. And make multimodal containers with it.</p>
</div>
<code>
<span class="code_header">~> python<br></span>
mdata = MuData({<br>
'rna': adata_rna,<br>
'prot': adata_prot<br>
})
</code>
<div>
<p>Generate <a href="https://muon.readthedocs.io/en/latest/omics/multi.html#multi-omics-factor-analysis" target="_blank">an interpretable latent space</a> leveraging information from multiple modalities. Or <a href="https://muon.readthedocs.io/en/latest/omics/multi.html#multiplex-clustering" target="_blank">cluster</a> your data based on multiple layers of information. Or construct <a href="https://muon.readthedocs.io/en/latest/omics/multi.html#weighted-nearest-neighbours" target="_blank">a neighbourhood graph</a> on multiple modalities.</p>
</div>
<code>
<span class="code_header">~> python<br></span>
mu.tl.mofa(mdata)
</code>
<div>
<p>Visualize results in and across modalities.</p>
</div>
<code>
<span class="code_header">~> python<br></span>
mu.pl.mofa(mdata, color='CD45RA')<br>
mu.pl.umap(mdata, color='celltype')
</code>
<div class="content_page_br"></div>
</div>
<div id="engage" class="content_page">
<!-- <h1>Engage with the community</h1> -->
<h1>get involved</h1>
<div>
<p>From biomedical observations to novel single-cell assays. From chromatin accessibility to spatial transcriptomics. Applications of multimodal data are far-reaching, and it's a community effort.</p>
</div>
</div>
<div class="content_page_wide">
<div id="green_canvas">
<div id="canvas_wrapper">
<div class="canvas_column">
<div>
<span>codebase</span>
<ul>
<li><a href="https://github.com/scverse/muon" target="_blank">source code</a></li>
<li><a href="https://github.com/scverse/muon-tutorials" target="_blank">tutorials</a></li>
<li><a href="https://github.com/scverse/mudata" target="_blank">mudata</a></li>
<li><a href="https://github.com/pmbio/mudatasets" target="_blank">mudatasets</a></li>
<li><a href="https://github.com/scverse/Muon.jl" target="_blank">Muon.jl</a></li>
<li><a href="https://github.com/pmbio/MuDataSeurat" target="_blank">MuDataSeurat</a></li>
<li><a href="https://github.com/pmbio/MuDataMAE" target="_blank">MuData (bioconductor)</a></li>
</ul>
</div>
<div>
<span>documentation</span>
<ul>
<li><a href="https://muon.readthedocs.io/en/latest/index.html" target="_blank">muon documentation</a></li>
<li><a href="https://muon-tutorials.readthedocs.io/en/latest/index.html" target="_blank">muon tutorials</a></li>
<li><a href="https://mudata.readthedocs.io/en/latest/index.html" target="_blank">mudata documentation</a></li>
</ul>
</div>
</div>
<div class="canvas_column">
<div>
<span>publications</span>
<ul>
<li><a href="https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02577-8" target="_blank">muon paper</a></li>
<li><a href="https://www.nature.com/articles/s41587-023-01733-8" target="_blank">scverse paper</a></li>
<li><a href="https://www.nature.com/articles/s41592-021-01343-9" target="_blank">MEFISTO paper</a></li>
<li><a href="https://genomebiology.biomedcentral.com/articles/10.1186/s13059-020-02015-1" target="_blank">MOFA+ paper</a></li>
</ul>
</div>
</div>
<div class="canvas_column">
<div>
<span>communication</span>
<ul>
<li><a href="https://scverse.zulipchat.com/" target="_blank">Zulip scverse server</a></li>
<li><a href="https://discourse.scverse.org/" target="_blank">Discourse scverse forum</a></li>
<li><a href="https://github.com/scverse/muon/discussions" target="_blank">GitHub discussions</a> & <a href="https://github.com/scverse/muon/issues" target="_blank">tracker</a></li>
<li><a href="https://join.slack.com/t/mofahelp/shared_invite/enQtMjcxNzM3OTE3NjcxLWNhZmM1MDRlMTZjZWRmYWJjMGFmMDkzNDBmMDhjYmJmMzdlYzU4Y2EzYTI1OGExNzM2MmUwMzJkZmVjNDkxNGI" target="_blank">Slack MOFA workspace</a></li>
</ul>
</div>
<div>
<span>main contributors</span>
<ul>
<li><a href="https://github.com/gtca" target="_blank">Danila Bredikhin</a></li>
<li><a href="https://github.com/ilia-kats" target="_blank">Ilia Kats</a></li>
<li><a href="https://github.com/mffrank" target="_blank">Max Frank</a></li>
</ul>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
<footer>
<div id="footer_content">
<div>
<p>Consider citing<br/><a href="https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02577-8">Bredikhin et al., 2022. MUON: multimodal omics analysis framework.</a></p>
</div>
<div>
<p>Page content and design by Danila Bredikhin.</p>
</div>
</div>
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updatePosition: function(event) {
var e = event || window.event;
this.x = e.clientX - this._x;
this.y = (e.clientY - this._y) * ((e.clientY - this._y) < 0 ? -1 : 1);
},
setOrigin: function(e) {
this._x = e.offsetLeft + Math.floor(e.offsetWidth / 2);
this._y = 0 + Math.floor(e.offsetHeight / 2);
},
show: function() {
return "(" + this.x + ", " + this.y + ")";
}
};
// Track the mouse position relative to the center of the container.
mouse.setOrigin(container);
//----------------------------------------------------
var counter = 0;
var refreshRate = 10;
var isTimeToUpdate = function() {
return counter++ % refreshRate === 0;
};
//----------------------------------------------------
var onMouseEnterHandler = function(event) {
update(event);
};
var onMouseLeaveHandler = function() {
inner.style = "";
};
var onMouseMoveHandler = function(event) {
if (isTimeToUpdate()) {
update(event);
}
};
//----------------------------------------------------
var update = function(event) {
mouse.updatePosition(event);
updateTransformStyle(
(mouse.y / inner.offsetHeight / 2).toFixed(2),
(mouse.x / inner.offsetWidth / 2).toFixed(2)
);
};
var updateTransformStyle = function(x, y) {
var style = "rotateX(" + x + "deg) rotateY(" + y + "deg)";
inner.style.transform = style;
inner.style.webkitTransform = style;
inner.style.mozTranform = style;
inner.style.msTransform = style;
inner.style.oTransform = style;
};
//--------------------------------------------------------
container.onmousemove = onMouseMoveHandler;
container.onmouseleave = onMouseLeaveHandler;
container.onmouseenter = onMouseEnterHandler;
})();
</script>
</body>
</html>