cellprofiler

CellProfiler on Terra

Run a single CellProfiler pipeline on Terra.

Pipelines

1. cellprofiler_pipeline.wdl

A basic workflow to run a custom .cppipe CellProfiler pipeline on Terra.
The pipeline can be specified as usual for a headless CellProfiler run. Just pass the .cppipe file and a path to the relevant images in a google bucket, and the workflow will spin up one or more VMs on Google Cloud, per your specifications, and run the CellProfiler pipeline there. Output can either be a tarball (called "output.tar.gz", and located wherever Terra chooses) or the output files can optionally be extracted and copied to a Google bucket location of choice (see the optional input output_directory_gsurl).

Required inputs:

• input_directory_gsurl: gsURL of Google bucket with image files
• cppipe_file: gsURL path to .cppipe file that specifies the CellProfiler pipeline
• xml_file: gsURL path to the XML file produced by the microscope
• config_yaml: gsURL path to a .yaml file, created by the user, that specifies important metadata about the experiment, including color channels

Optional inputs:

• output_directory_gsurl: If specified as a gsURL path, the output files will all be put here (WARNING: this will overwrite data in this bucket path!). If not specified, the outputs will be packaged as a tarball, and can be located using Terra.
• cellprofiler_docker_image: Can specify a different docker image than the default.
• hardware_preemptible_tries: Pre-emptible runs are cheaper, but you might be kicked off the VM in the middle of your run (i.e. you might be "pre-empted").
  This integer number specifies the number of times to try to execute the workflow using a pre-emptible machine. After this many tries, the workflow will run to completion using a non-preemptible VM (if it hasn't already completed). But each time the workflow is pre-empted, it must start over. This can lead to longer runs.

Other optional inputs concern the VM hardware for the cloud machine that will run CellProfiler, the most important of which are cellprofiler.hardware_cpu_count and cellprofiler.hardware_disk_size_GB and cellprofiler.hardware_memory_GB, which should be tuned to match the computational load being run.