added case study links to getting started section adn reordered getti…

…ng started, put interacting-with-viz at the top

docs/_build_html/_sources/getting_started.txt

@@ -3,11 +3,35 @@ Getting Started
 
 Clustergrammer is a web-based tool for visualizing and analyzing high-dimensional data as interactive and shareable hierarchically clustered heatmaps. Clustergrammer can be used in three main ways:
 
-#. :ref:`clustergrammer_web` (`http://amp.pharm.mssm.edu/clustergrammer`_)
+#. :ref:`clustergrammer_web`: `http://amp.pharm.mssm.edu/clustergrammer`_
 #. :ref:`clustergrammer_widget`
 #. :ref:`clustergrammer_js` and :ref:`clustergrammer_py` libraries
 
-This section will provide instructions on how to quickly visualize your data using the :ref:`clustergrammer_web` and the :ref:`clustergrammer_widget` as well as instructions on how to interact with the visualization. See :ref:`case_studies` to see how Clustergrammer can be used to explore and analyze real world data. For developers interested in building their own web page using Clustergrammer, please refer to the :ref:`building_web_page` section.
+This section will provide information on how to interact with the visualization and how to quickly visualize your own data using the :ref:`clustergrammer_web` and the :ref:`clustergrammer_widget`. See :ref:`case_studies` for examples of how Clustergrammer can be used to explore and analyze real world data. For developers interested in building their own web page using Clustergrammer, please refer to the :ref:`building_web_page` section.
+
+Interacting with Clustergrammer Heatmaps
+========================================
+Clustergrammer produces highly interactive visualizations that enable intuitive exploration of high-dimensional data including:
+
+- :ref:`zooming_and_panning`
+- :ref:`row_col_reordering` (e.g. reorder based on sum)
+- :ref:`interactive_dendrogram`
+- :ref:`interactive_dim_reduction` (e.g. filter rows based on variance)
+- :ref:`interactive_categories`
+- :ref:`crop`
+- :ref:`row_search`
+
+Press play or interact with the gene-expression demo below to see some of Clustergrammer's interactive features and see :ref:`interacting_with_viz` for more information:
+
+.. raw:: html
+
+   <iframe id='iframe_preview' src="https://amp.pharm.mssm.edu/clustergrammer/demo/" frameBorder="0" style='height: 495px; width:730px; margin-bottom:15px;'></iframe>
+
+Clustergrammer also has :ref:`biology_specific_features` for working with gene-level data including:
+
+- Mouseover gene names and description look-up (using `Harmonizome`_)
+- Enrichment analysis to find biological information (e.g. up-stream transcription factors) specific to your set of genes (using `Enrichr`_)
+
 
 .. _getting_started_web_app:
 
@@ -53,11 +77,15 @@ Clustergrammer-Widget
 =====================
 Jupyter notebooks are ideal for generating reproducible workflows and analysis. They are also the best way to share Clustergrammer's interactive visualizations while providing context, analysis, and the underlying data to enable reproducibility (see :ref:`clustergrammer_widget_examples`). The :ref:`clustergrammer_widget` enables users to easily produce interactive visualizations within a `Jupyter`_ notebook that can be shared with collaborators (using `nbviewer`_). The :ref:`clustergrammer_widget` can be used to visualize a matrix of data from a matrix file or from a `Pandas`_ DataFrame (see :ref:`matrix_format_io` for more information).
 
-Clustergrammer has been applied to visualize and analyze a wide variety of biological and non-biological data. See the Jupyter notebook examples below:
+Clustergrammer has been applied to visualize and analyze a wide variety of biological and non-biological data. See the Jupyter notebook examples below and :ref:`case_studies` for more information:
 
 - `Running_clustergrammer_widget.ipynb`_
 - `DataFrame_Example.ipynb`_
-- `Single Cell RNA-seq Visualization.ipynb`_
+- `CCLE Jupyter Notebook`_
+- `Lung Cancer PTM and Gene Expression Regulation`_
+- `Single-Cell CyTOF Data`_
+- `MNIST Notebook`_
+- `USDA Nutrient Dataset`_
 - `Iris Dataset.ipynb`_
 
 
@@ -94,29 +122,6 @@ See the screenshot below for an example widget visualization:
 
 Users can download and reproduce the example notebook, `Running_clustergrammer_widget.ipynb`_, by cloning its `GitHub repo`_. For more information about using the widget (e.g. visualizing data from a Pandas DataFrame and sharing notebooks) see :ref:`clustergrammer_widget`.
 
-Interacting with Clustergrammer
-===============================
-Clustergrammer produces highly interactive visualizations that enable intuitive exploration of high-dimensional data including:
-
-- :ref:`zooming_and_panning`
-- :ref:`row_col_reordering` (e.g. reorder based on sum)
-- :ref:`interactive_dendrogram`
-- :ref:`interactive_dim_reduction` (e.g. filter rows based on variance)
-- :ref:`interactive_categories`
-- :ref:`crop`
-- :ref:`row_search`
-
-Press play or interact with the gene-expression demo below to see some of Clustergrammer's interactive features and see :ref:`interacting_with_viz` for more information:
-
-.. raw:: html
-
-   <iframe id='iframe_preview' src="https://amp.pharm.mssm.edu/clustergrammer/demo/" frameBorder="0" style='height: 495px; width:730px; margin-bottom:15px;'></iframe>
-
-Clustergrammer also has :ref:`biology_specific_features` for working with gene-level data including:
-
-- Mouseover gene names and description look-up (using `Harmonizome`_)
-- Enrichment analysis to find biological information (e.g. up-stream transcription factors) specific to your set of genes (using `Enrichr`_)
-
 
 .. _`example visualization`: http://amp.pharm.mssm.edu/clustergrammer/viz_sim_mats/58a492b4a63cb826f0be6476/rc_two_cats.txt
 .. _`Enrichr`: http://amp.pharm.mssm.edu/Enrichr/
@@ -135,6 +140,14 @@ Clustergrammer also has :ref:`biology_specific_features` for working with gene-l
 
 .. _`DataFrame_Example.ipynb`: http://nbviewer.jupyter.org/github/MaayanLab/clustergrammer-widget/blob/master/DataFrame_Example.ipynb
 
-.. _`Single Cell RNA-seq Visualization.ipynb`: http://nbviewer.jupyter.org/github/MaayanLab/single_cell_RNAseq_Visualization/blob/master/Single%20Cell%20RNAseq%20Visualization%20Example.ipynb
+.. _`Lung Cancer PTM and Gene Expression Regulation`: http://nbviewer.jupyter.org/github/MaayanLab/CST_Lung_Cancer_Viz/blob/master/notebooks/CST_Data_Viz.ipynb
+
+.. _`Single-Cell CyTOF Data`: http://nbviewer.jupyter.org/github/MaayanLab/Cytof_Plasma_PMA/blob/master/notebooks/Plasma_vs_PMA_Phosphorylation.ipynb
+
+.. _`Iris Dataset.ipynb`: http://nbviewer.jupyter.org/github/MaayanLab/iris_clustergrammer_visualization/blob/master/Iris%20Dataset.ipynb
+
+.. _`CCLE Jupyter Notebook`: http://nbviewer.jupyter.org/github/MaayanLab/CCLE_Clustergrammer/blob/master/notebooks/Clustergrammer_CCLE_Notebook.ipynb
+
+.. _`MNIST Notebook`: http://nbviewer.jupyter.org/github/MaayanLab/MNIST_heatmaps/blob/master/notebooks/MNIST_Notebook.ipynb#Visualize-Downsampled-Version-of-MNIST
 
-.. _`Iris Dataset.ipynb`: http://nbviewer.jupyter.org/github/MaayanLab/iris_clustergrammer_visualization/blob/master/Iris%20Dataset.ipynb
+.. _`USDA Nutrient Dataset`: http://nbviewer.jupyter.org/github/MaayanLab/USDA_Nutrients_Viz/blob/master/USDA_Nutrients.ipynb

docs/_build_html/_sources/index.txt

@@ -11,7 +11,7 @@ Clustergrammer is a web-based tool for visualizing and analyzing high-dimensiona
 Using Clustergrammer
 ====================
 
-The easiest ways to use Clustergrammer to produce an interactive visualization of your data are:
+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`_)