Updating Azure and general marketplace info

README.md

@@ -124,31 +124,26 @@ After the test data has been successfully copied to HDFS you can run examples sc
 
 Note: if you installed the data to a non default location the `VS_DATA_DIR` needs to be set accordingly when running the examples
 
-#### Databricks notebook examples
+### VariantSpark on the cloud
 
-For convenience we have also provided a sample end-to-end variant-spark workflow
-in a Databricks (Jupyter-style) notebook for Spark 2.2. The examples, using a synthetic phenotype (Hipster-index)
-can be found in the `notebook-examples` folder of this repository.
+VariantSpark can easily be used in AWS and Azure. For more examples and information, check the [cloud folder](https://github.com/aehrc/VariantSpark/tree/master/cloud). For a quick start, check the few pointers below.
 
-To use an example:
+#### AWS Marketplace
 
-1. **Create** a free, community [Databricks](https://databricks.com/) account
-2. **Download** the `VariantSpark_HipsterIndex_Spark2.2.scala` file. Databricks notebook is for Spark 2.2 (scala 2.11)
-3. **Import** the notebook file into your Databricks instance. Read the instructions in the notebook on how to import a new library to use the `variant-spark` library.
-4. **Start** a cluster (be sure to select the version of Spark and Scala specified in the notebook). Wait up to 5 minutes for the cluster to be ready.
-5. **Attach** the notebook to the cluster
-6. **Run** the sample notebook
+VariantSpark is now available on [AWS Marketplace](https://aws.amazon.com/marketplace/pp/AEHRC-VariantSpark-Notebook/B07YVND4TD). Please read the [Guidlines](contributions/AwsMarketplace/README.md) for specification and step-by-step instructions.
+
+#### Azure Databricks
+
+VariantSpark can be easily deployed in Azure Databricks through the button below. Please read the [VariantSpark azure manual](https://github.com/aehrc/VariantSpark-Azure-deployment) for specification and step-by-step instructions.
+
+[![Deploy to Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2Faehrc%2FVariantSpark-Azure-deployment%2Fmaster%2Fazuredeploy.json)
 
 ### Contributions
 
 #### JsonRfAnalyser
 
 [JsonRfAnalyser](contributions/JsonRfAnalyser) is a python program that looks into the JSON RandomForest model and list variables on each tree and branch. Please read [README](contributions/JsonRfAnalyser/README.md) to see the complete list of functionalities.
 
-#### VariantSpark on AWS Marketplace
-
-VariantSpark is now available on [AWS Marketplace](https://aws.amazon.com/marketplace/pp/AEHRC-VariantSpark-Notebook/B07YVND4TD). Please read the [Guidlines](contributions/AwsMarketplace/README.md) for specification and step-by-step instructions.
-
 #### WebVisualiser
 
 [rfview.html](contributions/WebVisualiser/rfview.html) is a web program (run locally on your machine) where you can upload the json model produced by variantspark and it visualises trees in the model. You can identify which tree to be visualised. Node color and node labels could be set to different parameters such as number of samples in the node or the node impurity. It uses [vis.js](https://visjs.org/) for tree Visualisation.