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• Introduction to the CLC Genomics Cloud
  • Overview of CLC Genomics Cloud
  • CLC Genomics Cloud requirements
  • Contact information
  • Installing the CLC Cloud Module
    • Licensing modules
    • Uninstalling modules
  • Installing the Cloud Server Plugin
• Setting up CLC Genomics Cloud resources on AWS
  • Setting up AWS resources
  • Adding more AWS Batch queues for CLC jobs
  • Adding more AWS IAM users
  • Deleting or redeploying CLC Genomics Cloud infrastructure on AWS
• Using a CLC Workbench to work on the cloud
  • Prerequisites for working on the cloud using a Workbench
  • Configuring an AWS Connection in the Workbench
  • Submitting analyses to AWS from a Workbench
  • Working with AWS S3 using the Remote Files tab
  • Accessing results from the Processes tab
• Using a CLC Server to work on the cloud
  • Benefits of submitting jobs via a CLC Server
  • AWS Connections in the CLC Server
  • Configuring cloud presets
  • Browse AWS S3 locations
  • Submitting workflows to the cloud via a CLC Server using a CLC Workbench
  • Submitting workflows to the cloud using the CLC Server Command Line Tools
• Integrating third party tools into CLC software
  • Installing external applications in a CLC Workbench
• General information about inputs and results
  • General information about input data for cloud analyses
    • Reference data for analyses on the cloud
    • Using locally held data for analyses on AWS S3
  • General information about outputs from cloud analyses
• Monitoring and reviewing CLC cloud jobs
  • Using a CLC Workbench to monitor and review cloud jobs
  • Using a CLC Server to monitor and review cloud jobs
  • Using the AWS Console to monitor and review cloud jobs
• Appendix
  • Standard AWS Batch queues for CLC Genomics Cloud
  • AWS Batch queues, compute environments, AMIs and images
  • System file retention policies
  • Making custom plugins available for cloud analyses

Making custom plugins available for cloud analyses

Tools^8.1 delivered by custom CLC plugins are supported for cloud analyses when:

• Server plugins are placed in a plugin repository that has the expected file organization (described below).
• The server plugins have the name <workbench_plugin_id>.cpa.
• The location of the custom plugin repository is configured when setting up the standard CLC Genomics Cloud infrastructure on AWS, as described at Establishing resources on AWS.

When the above requirements have been met, analyses using tools delivered by a custom plugin can be run on the cloud. The corresponding plugin in the custom repository is used for the cloud-based execution.

Custom plugin repository structure

The custom plugin repository must have the structure and contents defined below. The term <workbench_plugin_id> refers to the value of that field in the plugin.properties file.

• A top level folder per plugin. The folder name must be <workbench_plugin_id>.
• A subfolder named server.
• Within the server folder, a subfolder with the name of the version of the plugin. e.g. "23.0" or "22.0.2".

  This name must be the version of the plugin. This may be different to the version or your CLC Workbench or CLC Server.

• The plugin .cpa file and any other relevant files (e.g. plugin.properties) must be placed in this folder.

  The plugin .cpa file must be named as <workbench_plugin_id>.cpa.

For example, a server plugin with the <workbench_plugin_id value example_plugin and version 23.0, the following structure in the plugin repository would be expected:

example_plugin/
                   server/
                            23.0/
                                  example_plugin.cpa
                                  plugin.properties

When a job is launched to run on the cloud, the exact version of the plugin in the CLC Workbench or CLC Server must be available in the repository. If it is not, the job will fail.

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Footnotes

...Tools^8.1

Only tools that can be used within workflows can be submitted to run on a CLC Genomics Cloud. Tools that are not workflow-enabled cannot be run on the cloud.

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