removed old scRNA-seq example

cornhundred · Jul 15, 2019 · 22e6978 · 22e6978
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diff --git a/docs/_build_html/.doctrees/case_studies.doctree b/docs/_build_html/.doctrees/case_studies.doctree
diff --git a/docs/_build_html/.doctrees/environment.pickle b/docs/_build_html/.doctrees/environment.pickle
diff --git a/docs/_build_html/_sources/case_studies.rst.txt b/docs/_build_html/_sources/case_studies.rst.txt
@@ -107,10 +107,6 @@ Zika Virus RNA-seq Data Visualization
 =====================================
 Clustergrammer was used to visualize the results of an RNA-Seq data analysis pipeline within a Jupyter notebook: `An open RNA-Seq data analysis pipeline tutorial with an example of reprocessing data from a recent Zika virus study`_ (`Wang et al.`_).
 
-Single-Cell RNA-seq Data Visualization
-======================================
-Clustergrammer was used to visualize published single-cell gene expression data: `Single-Cell RNA-seq Data Visualization`_ (`Olsson et al.`_). The visualization was produced using an Excel file provided alongside the figures.
-
 
 .. _`Kinase Substrate Similarity Network`: https://maayanlab.github.io/kinase_substrate_similarity_network/
 .. _`MNIST Data`: http://yann.lecun.com/exdb/mnist/

diff --git a/docs/_build_html/case_studies.html b/docs/_build_html/case_studies.html
@@ -29,8 +29,8 @@
   <link rel="stylesheet" href="https://unpkg.com/font-awesome@4.5.0/css/font-awesome.min.css" type="text/css" />
     <link rel="index" title="Index" href="genindex.html" />
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-    <link rel="next" title="Interacting with the Visualization" href="interacting_with_viz.html" />
-    <link rel="prev" title="Clustergrammer2 Widget" href="clustergrammer2.html" /> 
+    <link rel="next" title="Clustergrammer-Web" href="clustergrammer_web.html" />
+    <link rel="prev" title="Getting Started" href="getting_started.html" /> 
 
 
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@@ -85,8 +85,6 @@
 
               <ul class="current">
 <li class="toctree-l1"><a class="reference internal" href="getting_started.html">Getting Started</a></li>
-<li class="toctree-l1"><a class="reference internal" href="clustergrammer_web.html">Clustergrammer Web App</a></li>
-<li class="toctree-l1"><a class="reference internal" href="clustergrammer2.html">Clustergrammer2 Widget</a></li>
 <li class="toctree-l1 current"><a class="current reference internal" href="#">Case Studies and Tutorials</a><ul>
 <li class="toctree-l2"><a class="reference internal" href="#single-cell-gene-expression-2-700-pbmc">Single Cell Gene Expression 2,700 PBMC</a><ul>
 <li class="toctree-l3"><a class="reference internal" href="#view-interactive-notebook">View Interactive Notebook</a></li>
@@ -99,9 +97,10 @@
 <li class="toctree-l2"><a class="reference internal" href="#large-network-kinase-substrate-similarity-network">Large Network: Kinase Substrate Similarity Network</a></li>
 <li class="toctree-l2"><a class="reference internal" href="#machine-learning-and-miscellaneous-datasets">Machine Learning and Miscellaneous Datasets</a></li>
 <li class="toctree-l2"><a class="reference internal" href="#zika-virus-rna-seq-data-visualization">Zika Virus RNA-seq Data Visualization</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#single-cell-rna-seq-data-visualization">Single-Cell RNA-seq Data Visualization</a></li>
 </ul>
 </li>
+<li class="toctree-l1"><a class="reference internal" href="clustergrammer_web.html">Clustergrammer-Web</a></li>
+<li class="toctree-l1"><a class="reference internal" href="clustergrammer2.html">Clustergrammer2 Widget</a></li>
 <li class="toctree-l1"><a class="reference internal" href="interacting_with_viz.html">Interacting with the Visualization</a></li>
 <li class="toctree-l1"><a class="reference internal" href="biology_specific_features.html">Biology-Specific Features</a></li>
 <li class="toctree-l1"><a class="reference internal" href="matrix_format_io.html">Matrix Formats and Input/Output</a></li>
@@ -205,15 +204,15 @@ <h3>Run Notebook on the Cloud<a class="headerlink" href="#run-notebook-on-the-cl
 </div>
 <div class="section" id="cancer-cell-line-encyclopedia-gene-expression-data">
 <h2>Cancer Cell Line Encyclopedia Gene Expression Data<a class="headerlink" href="#cancer-cell-line-encyclopedia-gene-expression-data" title="Permalink to this headline">¶</a></h2>
-<div class="figure align-left" id="id2">
+<div class="figure align-left" id="id1">
 <a class="reference external image-reference" href="https://maayanlab.github.io/CCLE_Clustergrammer/"><img alt="CCLE Explorer" src="_images/CCLE_explorer.png" style="width: 800px;" /></a>
 <p class="caption"><span class="caption-text">Screenshot from the <a class="reference external" href="http://amp.pharm.mssm.edu/clustergrammer/CCLE/">CCLE Explorer</a> showing the tissue breakdown of the CCLE. Clicking on a tissue brings up an interactive heatmap with the top 250 most variable genes within a tissue. Also see the <a class="reference external" href="http://nbviewer.jupyter.org/github/MaayanLab/CCLE_Clustergrammer/blob/master/notebooks/Clustergrammer_CCLE_Notebook.ipynb">CCLE Jupyter Notebook</a> for an example of how to explore the CCLE gene expression data in a Jupyter notebook.</span></p>
 </div>
 <p>The Cancer Cell Line Encyclopedia (<a class="reference external" href="https://portals.broadinstitute.org/ccle/home">CCLE</a>) is a publicly available project that has characterized (e.g. genetic characterization) over 1,000 cancer cell lines. We used Clustergrammer to re-analyze and visualize CCLE’s gene expression data in the <a class="reference external" href="http://amp.pharm.mssm.edu/clustergrammer/CCLE/">CCLE Explorer</a>. The CCLE Explorer allows users to explore the CCLE by tissue type and visualize the most commonly differentially expressed genes for each tissue type as an interactive heatmap. The <a class="reference external" href="http://nbviewer.jupyter.org/github/MaayanLab/CCLE_Clustergrammer/blob/master/notebooks/Clustergrammer_CCLE_Notebook.ipynb">CCLE Jupyter Notebook</a> generates an overview of the CCLE gene expression data, investigates specific tissues, and explains how to use <a class="reference internal" href="biology_specific_features.html#enrichrgram"><span class="std std-ref">Enrichrgram</span></a> to understand the biological functions of differentially expressed genes.</p>
 </div>
 <div class="section" id="lung-cancer-post-translational-modification-and-gene-expression-regulation">
 <h2>Lung Cancer Post-Translational Modification and Gene Expression Regulation<a class="headerlink" href="#lung-cancer-post-translational-modification-and-gene-expression-regulation" title="Permalink to this headline">¶</a></h2>
-<div class="figure align-left" id="id3">
+<div class="figure align-left" id="id2">
 <a class="reference external image-reference" href="http://nbviewer.jupyter.org/github/MaayanLab/CST_Lung_Cancer_Viz/blob/master/notebooks/CST_Data_Viz.ipynb"><img alt="CST Screenshot" src="_images/CST_screenshot.png" style="width: 450px;" /></a>
 <p class="caption"><span class="caption-text">Screenshot from the <a class="reference external" href="http://nbviewer.jupyter.org/github/MaayanLab/CST_Lung_Cancer_Viz/blob/master/notebooks/CST_Data_Viz.ipynb?flush_cache=true">CST_Data_Viz.ipynb</a> Jupyter notebook showing hierarchical clustering of differential phosphorylation, methylation, acetylation, and gene expression data across 37 lung cancer cell lines. See the interactive Jupyter notebook <a class="reference external" href="http://nbviewer.jupyter.org/github/MaayanLab/CST_Lung_Cancer_Viz/blob/master/notebooks/CST_Data_Viz.ipynb?flush_cache=true">CST_Data_Viz.ipynb</a> for more information.</span></p>
 </div>
@@ -226,23 +225,23 @@ <h2>Lung Cancer Post-Translational Modification and Gene Expression Regulation<a
 </div>
 <div class="section" id="cytof-data-single-cell-immune-response-to-pma-treatment">
 <h2>CyTOF Data: Single Cell Immune Response to PMA Treatment<a class="headerlink" href="#cytof-data-single-cell-immune-response-to-pma-treatment" title="Permalink to this headline">¶</a></h2>
-<div class="figure align-left" id="id4">
+<div class="figure align-left" id="id3">
 <a class="reference external image-reference" href="http://nbviewer.jupyter.org/github/MaayanLab/Cytof_Plasma_PMA/blob/master/notebooks/Plasma_vs_PMA_Phosphorylation.ipynb"><img alt="CyTOF Screenshot" src="_images/CyTOF_screenshot.png" style="width: 450px;" /></a>
 <p class="caption"><span class="caption-text">Screenshot from the <a class="reference external" href="http://nbviewer.jupyter.org/github/MaayanLab/Cytof_Plasma_PMA/blob/master/notebooks/Plasma_vs_PMA_Phosphorylation.ipynb">Plasma_vs_PMA_Phosphrylation.ipynb</a> Jupyter notebook showing downsampled single cell CyTOF data (K-means downsampled from 220,000 single cells to 2,000 cell-clusters). Cell-clusters are shown as rows with cell-type categories (e.g. Natural Killer cells) and phosphorylations are shown as columns. See the interactive Jupyter notebook <a class="reference external" href="http://nbviewer.jupyter.org/github/MaayanLab/Cytof_Plasma_PMA/blob/master/notebooks/Plasma_vs_PMA_Phosphorylation.ipynb">Plasma_vs_PMA_Phosphrylation.ipynb</a> for more information.</span></p>
 </div>
 <p>White blood cells are a key component of the immune system and kinase signaling is known to play an important role in immune cell function (see <a class="reference external" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3831523/">Isakov and Altman 2013</a>). Our collaborators in the <a class="reference external" href="http://labs.icahn.mssm.edu/giannarellilab/">Giannarelli Lab</a> and the <a class="reference external" href="http://icahn.mssm.edu/research/portal/resources/deans-cores/human-immune-monitoring-core">Icahn School of Medicine Human Immune Monitoring Core</a> used Mass Cytometry, CyTOF (Fluidigm), to investigate the phosphorylation response of peripheral blood mononuclear cells (PBMC) immune cells exposed to PMA (phorbol 12-myristate 13-acetate), a tumor promoter and activator of protein kinase C (PKC). A total of 28 markers (18 surface markers and 10 phosphorylation markers) were measured in over 200,000 single cells. In the Jupyter notebook <a class="reference external" href="http://nbviewer.jupyter.org/github/MaayanLab/Cytof_Plasma_PMA/blob/master/notebooks/Plasma_vs_PMA_Phosphorylation.ipynb">Plasma_vs_PMA_Phosphrylation.ipynb</a> we semi-automatically identify cell types using surface markers and cluster cells based on phosphorylation to identify cell-type specific behavior at the phosphorylation level. See the <a class="reference external" href="http://nbviewer.jupyter.org/github/MaayanLab/Cytof_Plasma_PMA/blob/master/notebooks/Plasma_vs_PMA_Phosphorylation.ipynb">Plasma_vs_PMA_Phosphrylation.ipynb</a> Jupyter notebook for more information.</p>
 </div>
 <div class="section" id="large-network-kinase-substrate-similarity-network">
 <h2>Large Network: Kinase Substrate Similarity Network<a class="headerlink" href="#large-network-kinase-substrate-similarity-network" title="Permalink to this headline">¶</a></h2>
-<div class="figure align-left" id="id5">
+<div class="figure align-left" id="id4">
 <a class="reference external image-reference" href="https://maayanlab.github.io/kinase_substrate_similarity_network/"><img alt="Kinase Network Screenshot" src="_images/kinase_network_screenshot.png" style="width: 450px;" /></a>
 <p class="caption"><span class="caption-text">Screenshot from the <a class="reference external" href="https://maayanlab.github.io/kinase_substrate_similarity_network/">Kinase Substrate Similarity Network</a> example that demonstrates how Clustergrammer can be used to visualize a large network of kinases based on shared substrates.</span></p>
 </div>
 <p>Clustergrammer can be used to visualize large networks without the formation of ‘hairballs’. In the <a class="reference external" href="https://maayanlab.github.io/kinase_substrate_similarity_network/">Kinase Substrate Similarity Network</a> example we use Clustergrammer to visualize a network kinases based on shared substrate that includes 404 kinases and 163,216 links. Kinases are shown as rows and columns. For more information see the <a class="reference external" href="https://maayanlab.github.io/kinase_substrate_similarity_network/">Kinase Substrate Similarity Network</a> example.</p>
 </div>
 <div class="section" id="machine-learning-and-miscellaneous-datasets">
 <h2>Machine Learning and Miscellaneous Datasets<a class="headerlink" href="#machine-learning-and-miscellaneous-datasets" title="Permalink to this headline">¶</a></h2>
-<div class="figure align-left" id="id6">
+<div class="figure align-left" id="id5">
 <a class="reference external image-reference" href="http://nbviewer.jupyter.org/github/MaayanLab/MNIST_heatmaps/blob/master/notebooks/MNIST_Notebook.ipynb#Visualize-Downsampled-Version-of-MNIST"><img alt="MNIST Screenshot" src="_images/MNIST_screenshot.png" style="width: 450px;" /></a>
 <p class="caption"><span class="caption-text">Screenshot from the <a class="reference external" href="http://nbviewer.jupyter.org/github/MaayanLab/MNIST_heatmaps/blob/master/notebooks/MNIST_Notebook.ipynb">MNIST Notebook</a> that demonstrates how the <a class="reference internal" href="clustergrammer_widget.html#clustergrammer-widget"><span class="std std-ref">Clustergrammer-Widget</span></a> can be used to visualize the <a class="reference external" href="http://yann.lecun.com/exdb/mnist/">MNIST Data</a>. Downsampled handwritten digits (K-means downsampled from 70,0000 handwritten digits to 300 digit-clusters) are shown as columns with digit-type categories and pixels are shown as rows. For more information see the <a class="reference external" href="http://nbviewer.jupyter.org/github/MaayanLab/MNIST_heatmaps/blob/master/notebooks/MNIST_Notebook.ipynb">MNIST Notebook</a>.</span></p>
 </div>
@@ -258,10 +257,6 @@ <h2>Machine Learning and Miscellaneous Datasets<a class="headerlink" href="#mach
 <h2>Zika Virus RNA-seq Data Visualization<a class="headerlink" href="#zika-virus-rna-seq-data-visualization" title="Permalink to this headline">¶</a></h2>
 <p>Clustergrammer was used to visualize the results of an RNA-Seq data analysis pipeline within a Jupyter notebook: <a class="reference external" href="http://nbviewer.jupyter.org/github/maayanlab/Zika-RNAseq-Pipeline/blob/master/Zika.ipynb">An open RNA-Seq data analysis pipeline tutorial with an example of reprocessing data from a recent Zika virus study</a> (<a class="reference external" href="https://f1000research.com/articles/5-1574/v1">Wang et al.</a>).</p>
 </div>
-<div class="section" id="single-cell-rna-seq-data-visualization">
-<h2>Single-Cell RNA-seq Data Visualization<a class="headerlink" href="#single-cell-rna-seq-data-visualization" title="Permalink to this headline">¶</a></h2>
-<p>Clustergrammer was used to visualize published single-cell gene expression data: <a class="reference external" href="http://nbviewer.jupyter.org/github/MaayanLab/single_cell_RNAseq_Visualization/blob/master/Single%20Cell%20RNAseq%20Visualization%20Example.ipynb">Single-Cell RNA-seq Data Visualization</a> (<a class="reference external" href="http://www.nature.com/nature/journal/v537/n7622/full/nature19348.html">Olsson et al.</a>). The visualization was produced using an Excel file provided alongside the figures.</p>
-</div>
 </div>
 
 
@@ -272,10 +267,10 @@ <h2>Single-Cell RNA-seq Data Visualization<a class="headerlink" href="#single-ce
 
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-        <a href="interacting_with_viz.html" class="btn btn-neutral float-right" title="Interacting with the Visualization" accesskey="n" rel="next">Next <span class="fa fa-arrow-circle-right"></span></a>
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diff --git a/docs/_build_html/index.html b/docs/_build_html/index.html
@@ -247,7 +247,6 @@ <h2>Contents:<a class="headerlink" href="#contents" title="Permalink to this hea
 <li class="toctree-l2"><a class="reference internal" href="case_studies.html#large-network-kinase-substrate-similarity-network">Large Network: Kinase Substrate Similarity Network</a></li>
 <li class="toctree-l2"><a class="reference internal" href="case_studies.html#machine-learning-and-miscellaneous-datasets">Machine Learning and Miscellaneous Datasets</a></li>
 <li class="toctree-l2"><a class="reference internal" href="case_studies.html#zika-virus-rna-seq-data-visualization">Zika Virus RNA-seq Data Visualization</a></li>
-<li class="toctree-l2"><a class="reference internal" href="case_studies.html#single-cell-rna-seq-data-visualization">Single-Cell RNA-seq Data Visualization</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="clustergrammer_web.html">Clustergrammer-Web</a><ul>

diff --git a/docs/_build_html/searchindex.js b/docs/_build_html/searchindex.js
diff --git a/docs/case_studies.rst b/docs/case_studies.rst
@@ -107,10 +107,6 @@ Zika Virus RNA-seq Data Visualization
 =====================================
 Clustergrammer was used to visualize the results of an RNA-Seq data analysis pipeline within a Jupyter notebook: `An open RNA-Seq data analysis pipeline tutorial with an example of reprocessing data from a recent Zika virus study`_ (`Wang et al.`_).
 
-Single-Cell RNA-seq Data Visualization
-======================================
-Clustergrammer was used to visualize published single-cell gene expression data: `Single-Cell RNA-seq Data Visualization`_ (`Olsson et al.`_). The visualization was produced using an Excel file provided alongside the figures.
-
 
 .. _`Kinase Substrate Similarity Network`: https://maayanlab.github.io/kinase_substrate_similarity_network/
 .. _`MNIST Data`: http://yann.lecun.com/exdb/mnist/