GitHub - biojava/biojava-spark: :collision: Algorithms that are built around BioJava and run on Apache Spark

Algorithms that are built around BioJava and are running on Apache Spark

Starting up

Some initial instructions can be found on the mmtf-spark project

First download and untar a Hadoop sequence file of the PDB (~7 GB download)

wget http://mmtf.rcsb.org/v1.0/hadoopfiles/full.tar
tar -xvf full.tar

Or you can get a C-alpha, phosphate, ligand only version (~800 Mb download)

wget http://mmtf.rcsb.org/v1.0/hadoopfiles/reduced.tar
tar -xvf reduced.tar

Second add the biojava-spark dependecy to your pom

<dependency>
	<groupId>org.biojava</groupId>
	<artifactId>biojava-spark</artifactId>
	<version>0.2.1</version>
</dependency>

Extra Biojava examples

Do some simple quality filtering

float maxResolution = 3.0f;
float maxRfree = 0.3f;
StructureDataRDD structureData = new StructureDataRDD("/path/to/file")
			.filterResolution(maxResolution)
			.filterRfree(maxRfree);

Summarsing the elements in the PDB

Map<String, Long> elementCountMap = BiojavaSparkUtils.findAtoms(structureData).countByElement();

Finding inter-atomic contacts from the PDB

Double mean = BiojavaSparkUtils.findContacts(structureData,
		new AtomSelectObject()
				.groupNameList(new String[] {"PRO","LYS"})
				.elementNameList(new String[] {"C"})
				.atomNameList(new String[] {"CA"}),
				cutoff)
		.getDistanceDistOfAtomInts("CA", "CA")
		.mean();
System.out.println("\nMean PRO-LYS CA-CA distance: " + mean);