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README.md

THIS CODEBASE HAS BEEN DEPRECATED - WE ARE NO LONGER MAINTAINING IT.

PLEASE SEE https://github.com/broadinstitute/gatk INSTEAD

DEPRECATION NOTICE


GATK4-Protected (codename Hellbender-protected)

GATK4 development of the previously license-protected part of the toolkit. The contents of this repo will be merged into broadinstitute/gatk in the near future.

This README is aimed at developers. For user information, please see the GATK 4 forum

Read GATK 4 README

Please refer to the GATK 4 public repo README for general guidelines and how to setup your development environment.

Requirements

  • R 3.1.3 see additional requirements below: R package requirements

  • Java 8

  • (Developers) Gradle 2.13 is needed for building the GATK. We recommend using the ./gradlew script which will download and use an appropriate gradle version automatically.

  • (Developers) git lfs 1.1.0 (or greater) is needed for testing GATK-Protected builds. It is needed to download large files for the complete test suite. Run git lfs install after downloading, followed by git lfs pull to download the large files. The download is ~500 MB.

R Required Packages

R packages can be installed using the install_R_packages.R script inside the scripts directory.

Building GATK4

  • To do a fast build that lets you run GATK tools from within a git clone locally (but not on a cluster), run:

      ./gradlew installDist
    
  • To do a slower build that lets you run GATK tools from within a git clone both locally and on a cluster, run:

      ./gradlew installAll
    
  • To build a fully-packaged GATK jar that can be distributed and includes all dependencies needed for running tools locally, run:

      ./gradlew localJar
    
    • The resulting jar will be in build/libs with a name like gatk-protected-package-VERSION-local.jar
  • To build a fully-packaged GATK jar that can be distributed and includes all dependencies needed for running spark tools on a cluster, run:

      ./gradlew sparkJar
    
    • The resulting jar will be in build/libs with a name like gatk-protected-package-VERSION-spark.jar
    • This jar will not include Spark and Hadoop libraries, in order to allow the versions of Spark and Hadoop installed on your cluster to be used.
  • To remove previous builds, run:

      ./gradlew clean
    

Running GATK4

  • The standard way to run GATK4 tools is via the gatk-launch wrapper script located in the root directory of a clone of this repository.

    • Requires Python 2.6 or greater.
    • You need to have built the GATK as described in the "Building GATK4" section above before running this script.
    • There are three ways gatk-launch can be run:
      • from the root of your git clone after building
      • or, put the gatk-launch script within the same directory as fully-packaged GATK jars produced by ./gradlew localJar and ./gradlew sparkJar
      • or, the environment variables GATK_LOCAL_JAR and GATK_SPARK_JAR can be defined, and contain the paths to the fully-packaged GATK jars produced by ./gradlew localJar and ./gradlew sparkJar
    • Can run non-Spark tools as well as Spark tools, and can run Spark tools locally, on a Spark cluster, or on Google Cloud Dataproc.
  • For help on using gatk-launch itself, run ./gatk-launch --help

  • To print a list of available tools, run ./gatk-launch --list.

  • To print help for a particular tool, run ./gatk-launch ToolName --help.

  • To run a non-Spark tool, or to run a Spark tool locally, the syntax is:

    ./gatk-launch ToolName toolArguments
    

    Examples:

    ./gatk-launch PrintReads -I input.bam -O output.bam
    
    ./gatk-launch PrintReadsSpark -I input.bam -O output.bam
    
  • To run a Spark tool on a Spark cluster, the syntax is:

    ./gatk-launch ToolName toolArguments -- --sparkRunner SPARK --sparkMaster <master_url> additionalSparkArguments
    

    Example:

    ./gatk-launch PrintReadsSpark -I hdfs://path/to/input.bam -O hdfs://path/to/output.bam \
        -- \
        --sparkRunner SPARK --sparkMaster <master_url> \
        --num-executors 5 --executor-cores 2 --executor-memory 4g \
        --conf spark.yarn.executor.memoryOverhead=600
    
  • To run a Spark tool on Google Cloud Dataproc, the syntax is:

    ./gatk-launch ToolName toolArguments -- --sparkRunner GCS --cluster myGCSCluster additionalSparkArguments
    

    Example:

    ./gatk-launch PrintReadsSpark \
          -I gs://my-gcs-bucket/path/to/input.bam \
          -O gs://my-gcs-bucket/path/to/output.bam \
          -- \
          --sparkRunner GCS --cluster myGCSCluster \
          --num-executors 5 --executor-cores 2 --executor-memory 4g \
          --conf spark.yarn.executor.memoryOverhead=600
    
  • See the GATK4 public README for full instructions on using gatk-launch to run tools on a Spark/Dataproc cluster.

Testing GATK4

  • To run the tests, run ./gradlew test.

    • Test report is in build/reports/tests/test/index.html.
    • Note that git lfs must be installed and set up as described in the "Requirements" section above in order for all tests to pass.
  • To run a subset of tests, use gradle's test filtering (see gradle doc), e.g.,

    • ./gradlew test -Dtest.single=SomeSpecificTestClass
    • ./gradlew test --tests *SomeSpecificTestClass
    • ./gradlew test --tests all.in.specific.package*
    • ./gradlew test --tests *SomeTest.someSpecificTestMethod
  • See the GATK4 public README for further information on running tests.

The CNV case and PoN workflows (description and examples)

This can be found here

Running the CNV case and PoN creation Workflows with premade Queue scripts

For Broad Internal instructions

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