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.. _getting_started:

Getting Started
---------------

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Welcome to Clustergrammer's Documentation!
------------------------------------------
Clustergrammer is a web-based tool for visualizing and analyzing high-dimensional data as interactive and shareable hierarchically clustered heatmaps (see :ref:`intro_heatmap_clustergram`). Clustergrammer produces highly interactive visualizations that enable intuitive exploration of high-dimensional data and has several optional biology-specific features (e.g. enrichment analysis; see :ref:`biology_specific_features`) to facilitate the exploration of gene-level biological data. The project is free and open-source (all code is available on GitHub).
The Clustergrammer project consists of web-based tools for visualizing and analyzing high-dimensional data as interactive and shareable hierarchically clustered heatmaps (see :ref:`intro_heatmap_clustergram`). Clustergrammer produces highly interactive visualizations that enable intuitive exploration of high-dimensional data and has several optional biology-specific features (e.g. enrichment analysis; see :ref:`biology_specific_features`) to facilitate the exploration of gene-level biological data. The project is free, open-source (all code is available on GitHub), and being actively developed at the `Human Immune Monitoring Center`_ at the `Icahn School of Medicine at Mount Sinai`_.


Clustergrammer2
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<iframe width="560" height="315" src="https://www.youtube.com/embed/f-snXe2Bn9Q" frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe>
</div>

Clustergrammer is currently being re-built using the WebGL library `regl`_. Users can try out Clustergrammer2 on NBViewer, MyBinder, Kaggle, and Saturn.io (see :ref:`case_studies`).



Using Clustergrammer
====================

The easiest ways to use Clustergrammer to produce an interactive visualization of your data are to:

- upload a tab-separated matrix file using the Clustergrammer web app: `https://amp.pharm.mssm.edu/clustergrammer/`_
- or use the :ref:`clustergrammer_widget` within a `Jupyter`_ notebook and share using `nbviewer`_ (see `example notebook`_)

The :ref:`clustergrammer_web` is the quickest way to generate an interactive and shareable visualization (see `example visualization`_ and :ref:`getting started Web-app<getting_started_web_app>`). For users who want to visualize their data within a Jupyter notebook, the :ref:`clustergrammer_widget` enables visualizations to be embedded into shareable Jupyter notebooks (see `example notebook`_ and :ref:`Getting Started Widget <getting_started_widget>`).

Web developers can use Clustergrammer's core libraries, :ref:`clustergrammer_js` and :ref:`clustergrammer_py`, or the :ref:`clustergrammer_web_api` to dynamically generate visualizations for their own web applications (see examples in :ref:`app_integration`).

Please read the :doc:`getting_started` guide for more information.
Clustergrammer2 uses the WebGL library `regl`_ to handle larger single-cell datasets (e.g. scRNA-seq data) and enable researchers to interactively explore datasets consisting of millions of data points without the need for dimensionality reduction. Please see :ref:`case_studies` and :ref:`getting_started` for more information.

Case Studies and Examples
=========================
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<div itemprop="articleBody">

<div class="section" id="getting-started">
<h1>Getting Started<a class="headerlink" href="#getting-started" title="Permalink to this headline"></a></h1>
<span id="id1"></span><h1>Getting Started<a class="headerlink" href="#getting-started" title="Permalink to this headline"></a></h1>
<p>Clustergrammer is a web-based tool for visualizing and analyzing high-dimensional data as interactive and shareable hierarchically clustered heatmaps (see <a class="reference internal" href="interacting_with_viz.html#intro-heatmap-clustergram"><span class="std std-ref">Introduction to Clustergrams</span></a>).</p>
<div class="section" id="using-clustergrammer">
<h2>Using Clustergrammer<a class="headerlink" href="#using-clustergrammer" title="Permalink to this headline"></a></h2>
Expand Down Expand Up @@ -234,18 +234,18 @@ <h2>Interacting with Clustergrammer Heatmaps<a class="headerlink" href="#interac
<div class="section" id="clustergrammer-web-app">
<span id="getting-started-web-app"></span><h2>Clustergrammer Web-App<a class="headerlink" href="#clustergrammer-web-app" title="Permalink to this headline"></a></h2>
<p>Users can easily generate an interactive and shareable heatmap visualization using the <a class="reference internal" href="clustergrammer_web.html#clustergrammer-web"><span class="std std-ref">Clustergrammer-Web</span></a> (see upload section screenshot below). Simply upload a tab-separated matrix file (see <a class="reference internal" href="matrix_format_io.html#matrix-format-io"><span class="std std-ref">Matrix Formats and Input/Output</span></a> for more information) at the <a class="reference external" href="http://amp.pharm.mssm.edu/clustergrammer/">homepage</a> to be redirected to a permanent and shareable visualization of your data.</p>
<div class="figure align-left" id="id1">
<div class="figure align-left" id="id2">
<a class="reference external image-reference" href="http://amp.pharm.mssm.edu/clustergrammer/"><img alt="Clustergrammer Web" src="_images/clustergrammer_web_upload.png" style="width: 550px;" /></a>
<p class="caption"><span class="caption-text">Users can upload their data using the web app <a class="reference external" href="http://amp.pharm.mssm.edu/clustergrammer/">homepage</a>. Simply choose your file and upload to be redirected to your permanent and shareable visualization.</span></p>
</div>
<p>Once you upload your data, the <a class="reference internal" href="clustergrammer_web.html#clustergrammer-web"><span class="std std-ref">Clustergrammer-Web</span></a> clusters your data and produces three views: a heatmap of your input matrix, a similarity matrix of your columns, and a similarity matrix of your rows. See the screenshots below and the <a class="reference external" href="http://amp.pharm.mssm.edu/clustergrammer/viz_sim_mats/58a492b4a63cb826f0be6476/rc_two_cats.txt">example visualization</a> for an example results page.</p>
<p><strong>Heatmap View</strong></p>
<div class="figure align-left" id="id2">
<div class="figure align-left" id="id3">
<a class="reference external image-reference" href="http://amp.pharm.mssm.edu/clustergrammer/viz_sim_mats/58a492b4a63cb826f0be6476/rc_two_cats.txt"><img alt="Web application heatmap" src="_images/web_app_heatmap.png" style="width: 800px;" /></a>
<p class="caption"><span class="caption-text">Above is an example clustergram visualization produced by the <a class="reference internal" href="clustergrammer_web.html#clustergrammer-web"><span class="std std-ref">Clustergrammer-Web</span></a>. Clustergrammer produces three views of your data; the clustered heatmap view is shown above.</span></p>
</div>
<p><strong>Similarity Matrix View</strong></p>
<div class="figure align-left" id="id3">
<div class="figure align-left" id="id4">
<a class="reference external image-reference" href="http://amp.pharm.mssm.edu/clustergrammer/viz_sim_mats/58a492b4a63cb826f0be6476/rc_two_cats.txt"><img alt="Web application sim-mat" src="_images/web_app_sim_mat.png" style="width: 800px;" /></a>
<p class="caption"><span class="caption-text">Clustergrammer produces similarity matrices of rows and columns to provide additional perspectives on your data. Above is an example column similarity matrix.</span></p>
</div>
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<div class="section" id="welcome-to-clustergrammer-s-documentation">
<h1>Welcome to Clustergrammer’s Documentation!<a class="headerlink" href="#welcome-to-clustergrammer-s-documentation" title="Permalink to this headline"></a></h1>
<p>Clustergrammer is a web-based tool for visualizing and analyzing high-dimensional data as interactive and shareable hierarchically clustered heatmaps (see <a class="reference internal" href="interacting_with_viz.html#intro-heatmap-clustergram"><span class="std std-ref">Introduction to Clustergrams</span></a>). Clustergrammer produces highly interactive visualizations that enable intuitive exploration of high-dimensional data and has several optional biology-specific features (e.g. enrichment analysis; see <a class="reference internal" href="biology_specific_features.html#biology-specific-features"><span class="std std-ref">Biology-Specific Features</span></a>) to facilitate the exploration of gene-level biological data. The project is free and open-source (all code is available on GitHub).</p>
<p>The Clustergrammer project consists of web-based tools for visualizing and analyzing high-dimensional data as interactive and shareable hierarchically clustered heatmaps (see <a class="reference internal" href="interacting_with_viz.html#intro-heatmap-clustergram"><span class="std std-ref">Introduction to Clustergrams</span></a>). Clustergrammer produces highly interactive visualizations that enable intuitive exploration of high-dimensional data and has several optional biology-specific features (e.g. enrichment analysis; see <a class="reference internal" href="biology_specific_features.html#biology-specific-features"><span class="std std-ref">Biology-Specific Features</span></a>) to facilitate the exploration of gene-level biological data. The project is free, open-source (all code is available on GitHub), and being actively developed at the <a class="reference external" href="https://icahn.mssm.edu/research/human-immune-monitoring-center">Human Immune Monitoring Center</a> at the <a class="reference external" href="http://icahn.mssm.edu/">Icahn School of Medicine at Mount Sinai</a>.</p>
<div class="section" id="clustergrammer2">
<h2>Clustergrammer2<a class="headerlink" href="#clustergrammer2" title="Permalink to this headline"></a></h2>
<p><a class="reference external" href="https://mybinder.org/v2/gh/ismms-himc/clustergrammer2-examples/master?filepath=notebooks%2F1.0_Clustergrammer2_Example_Notebook.ipynb"><img alt="version" 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/></a> <a class="reference external" href="https://mybinder.org/v2/gh/ismms-himc/clustergrammer2_examples/master?filepath=notebooks%2F2.0_CCLE_Gene_Expression.ipynb"><img alt="version" src="https://img.shields.io/badge/launch-2.0%20CCLE%20Gene%20Expression-579ACA.svg?logo=data:image/png;base64,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" /></a></p>
<div style="position: relative; padding-bottom: 10px; height: 0; overflow: hidden; max-width: 100%; height: auto;">

<iframe width="560" height="315" src="https://www.youtube.com/embed/f-snXe2Bn9Q" frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe>
</div><p>Clustergrammer is currently being re-built using the WebGL library <a class="reference external" href="http://regl.party/">regl</a>. Users can try out Clustergrammer2 on NBViewer, MyBinder, Kaggle, and Saturn.io (see <a class="reference internal" href="case_studies.html#case-studies"><span class="std std-ref">Case Studies and Tutorials</span></a>).</p>
</div>
<div class="section" id="using-clustergrammer">
<h2>Using Clustergrammer<a class="headerlink" href="#using-clustergrammer" title="Permalink to this headline"></a></h2>
<p>The easiest ways to use Clustergrammer to produce an interactive visualization of your data are to:</p>
<ul class="simple">
<li>upload a tab-separated matrix file using the Clustergrammer web app: <a class="reference external" href="https://amp.pharm.mssm.edu/clustergrammer/">https://amp.pharm.mssm.edu/clustergrammer/</a></li>
<li>or use the <a class="reference internal" href="clustergrammer_widget.html#clustergrammer-widget"><span class="std std-ref">Clustergrammer-Widget</span></a> within a <a class="reference external" href="http://jupyter.org/">Jupyter</a> notebook and share using <a class="reference external" href="http://nbviewer.jupyter.org/">nbviewer</a> (see <a class="reference external" href="http://nbviewer.jupyter.org/github/MaayanLab/clustergrammer-widget/blob/master/Running_clustergrammer_widget.ipynb">example notebook</a>)</li>
</ul>
<p>The <a class="reference internal" href="clustergrammer_web.html#clustergrammer-web"><span class="std std-ref">Clustergrammer-Web</span></a> is the quickest way to generate an interactive and shareable visualization (see <a class="reference external" href="http://amp.pharm.mssm.edu/clustergrammer/viz_sim_mats/58a492b4a63cb826f0be6476/rc_two_cats.txt">example visualization</a> and <a class="reference internal" href="getting_started.html#getting-started-web-app"><span class="std std-ref">getting started Web-app</span></a>). For users who want to visualize their data within a Jupyter notebook, the <a class="reference internal" href="clustergrammer_widget.html#clustergrammer-widget"><span class="std std-ref">Clustergrammer-Widget</span></a> enables visualizations to be embedded into shareable Jupyter notebooks (see <a class="reference external" href="http://nbviewer.jupyter.org/github/MaayanLab/clustergrammer-widget/blob/master/Running_clustergrammer_widget.ipynb">example notebook</a> and <a class="reference internal" href="getting_started.html#getting-started-widget"><span class="std std-ref">Getting Started Widget</span></a>).</p>
<p>Web developers can use Clustergrammer’s core libraries, <a class="reference internal" href="clustergrammer_js.html#clustergrammer-js"><span class="std std-ref">Clustergrammer-JS</span></a> and <a class="reference internal" href="clustergrammer_py.html#clustergrammer-py"><span class="std std-ref">Clustergrammer-PY</span></a>, or the <a class="reference internal" href="clustergrammer_web.html#clustergrammer-web-api"><span class="std std-ref">Clustergrammer-Web API</span></a> to dynamically generate visualizations for their own web applications (see examples in <a class="reference internal" href="app_integration.html#app-integration"><span class="std std-ref">App Integrations</span></a>).</p>
<p>Please read the <a class="reference internal" href="getting_started.html"><span class="doc">Getting Started</span></a> guide for more information.</p>
</div><p>Clustergrammer2 uses the WebGL library <a class="reference external" href="http://regl.party/">regl</a> to handle larger single-cell datasets (e.g. scRNA-seq data) and enable researchers to interactively explore datasets consisting of millions of data points without the need for dimensionality reduction. Please see <a class="reference internal" href="case_studies.html#case-studies"><span class="std std-ref">Case Studies and Tutorials</span></a> and <a class="reference internal" href="getting_started.html#getting-started"><span class="std std-ref">Getting Started</span></a> for more information.</p>
</div>
<div class="section" id="case-studies-and-examples">
<h2>Case Studies and Examples<a class="headerlink" href="#case-studies-and-examples" title="Permalink to this headline"></a></h2>
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.. _getting_started:

Getting Started
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