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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

Using a CLC Workbench to work on the cloud

This chapter describes configuring and using a CLC Workbench to submit jobs for execution on AWS, as well as working with data on AWS S3, including uploading data to AWS S3.

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Subsections

• 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

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