Linking tutorial more prominently in home.md. (#37)

* Linking tutorial more prominently in home.md.

docs_manual/index.rst

@@ -11,9 +11,9 @@ Getting Started
 ---------------
 
 - you can find the **publically available web app** at https://scelvis-demo.bihealth.org.
-- to get started with your analysis, follow the :ref:`tutorial_analysis`.
+- to get started with your analysis, watch the `Movie <https://github.com/bihealth/scelvis#Movie>`_ or follow the :ref:`tutorial_analysis`.
 - to learn how to get your own data into SCelVis, read about :ref:`tutorial_input_formats`.
-- if you are a bioinformatician and interested in running your own SCelVis server, follow the :ref:`tutorial_cli`.
+- if you are a bioinformatician and interested in running your own SCelVis server, read the :ref:`tutorial_cli`.
 
 
 ------------------------

scelvis/static/home.md

@@ -1,25 +1,30 @@
-### ScelVis Quickstart
+### SCelVis
 
 SCelVis is a web app for the visualization and interactive exploration of single-cell transcriptomic data.
 
-**Start by selecting the dataset you want to work with from the `Go To` menu on the top right**:
-choose an existing dataset, or upload a new one.
+#### Quickstart
+
+- Start by selecting the dataset you want to work with from the `Go To` menu on the top right: choose an existing dataset, or upload a new one.
+- check out our [Documentation](https://scelvis.readthedocs.io/en/latest/index.html), in particular the [Tutorial](https://scelvis.readthedocs.io/en/latest/tutorial_analysis.html), or the movie on our [github page](https://github.com/bihealth/scelvis#Movie)
+- some example data to upload: [PBMCs](https://files.figshare.com/18037739/pbmc.h5ad), [human-mouse mix](https://github.com/bihealth/scelvis/raw/master/examples/hgmm_1k.h5ad).
+
+#### Main user interface
 
 ![go to https://github.com/bihealth/scelvis for an animated tutorial](https://raw.githubusercontent.com/bihealth/scelvis/master/scelvis/static/scelvis_screenshot.png)
 
 1. switch between tabs:
 
-  * `About`: information about dataset
-  * `Cell Annotation`: browse cell meta data
-  * `Gene Expression`: explore gene expression
+   - `About`: information about dataset
+   - `Cell Annotation`: browse cell meta data
+   - `Gene Expression`: explore gene expression
 
 2. select plot type
 
 3. open control panel to filter cells
 
 4. choose x- and y-axis of scatter plot (usually embeddings like tSNE or UMAP)
 
-5. perform differential expression analysis between groups of cells selected on the plt
+5. open control panel to perform differential expression analysis between groups of cells selected on the scatter plot
 
 6. hover over points on the plot to get more information