biojava/biojava-spark

Name: biojava-spark

Owner: BioJava

Description: :collision: Algorithms that are built around BioJava and run on Apache Spark

Created: 2016-04-29 18:06:39.0

Updated: 2017-09-05 13:33:48.0

Pushed: 2016-08-18 22:46:10.0

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Size: 67803

Language: Java

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README

BioJava-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

https://github.com/rcsb/mmtf-spark

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

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

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

 http://mmtf.rcsb.org/v1.0/hadoopfiles/reduced.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);