valyo/spark-vs

Intelligent virtual screening with confidence based on conformal prediction

Spark SBVS

Spark-VS is a Spark-based library for setting up massively parallel Structure-Based Virtual Screening (SBVS) pipelines in Spark.

Getting started

First, you need to setup a Spark project with maven, this tutorial is a good starting point: www.youtube.com/watch?v=aB4-RD_MMf0

Then, add the following entries into your pom.xml file:

<repositories>
	...
	<repository>
		<id>pele.farmbio.uu.se</id>
		<url>http://pele.farmbio.uu.se/artifactory/libs-snapshot</url>
	</repository>
	...
</repositories>

<dependencies>
...
	<groupId>se.uu.farmbio</groupId>
		<artifactId>vs</artifactId>
		<version>0.0.1-SNAPSHOT</version>
	</dependency>
...
</dependencies>

Finally, since OpenEye libraries are used under the hood, you need to own and a OpenEye license in order to run this. Therefore, you need to set a OE_LICENSE environment variable that points to the license, in your system to run the code in this repository.

Import vs.examples project in Scala IDE

1. File > Import > General > Existing project into workspace
2. Select vs.example as root directory
3. Click finish
4. Wait for the workspace to build (this can take a while) If the IDE asks to include the scala library or compiler in the workspace click No

If you have scala version problems follow this procedure:

1. Right click on the project foldel in the Package Explorer > Properties > Scala Compiler
2. Select fixed scala installation 2.10.X
3. Click apply and let the IDE clean the project

Now you can get familiar with Spark-VS giving a look to the examples, and running them in Scala IDE. In the data directory you can find an exaple SDF and SMILES files, as well as a receptor file. Remember that in order to run examples you need to specify arguments and OE_LICENSE environment variable through Run Configurations. Later on you may want to create your own project to write specific pipelines for your use case.