C-PAC/CPAC/resources/configs/pipeline_config_preproc.yml at 17ae48897190bf813a6d11b03423f04b10112da1 · FCP-INDI/C-PAC · GitHub

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%YAML 1.1
---
# CPAC Pipeline Configuration YAML file
# Version 1.8.8.dev2
#
# http://fcp-indi.github.io for more info.
#
# Tip: This file can be edited manually with a text editor for quick modifications.
FROM: default

pipeline_setup:

  # Name for this pipeline configuration - useful for identification.
  # This string will be sanitized and used in filepaths
  pipeline_name: cpac_preproc
  system_config:

    # Select Off if you intend to run CPAC on a single machine.
    # If set to On, CPAC will attempt to submit jobs through the job scheduler / resource manager selected below.
    on_grid:
      SGE:

        # SGE Parallel Environment to use when running CPAC.
        # Only applies when you are running on a grid or compute cluster using SGE.
        parallel_environment: cpac

    # The maximum amount of memory each participant's workflow can allocate.
    # Use this to place an upper bound of memory usage.
    # - Warning: 'Memory Per Participant' multiplied by 'Number of Participants to Run Simultaneously'
    #   must not be more than the total amount of RAM.
    # - Conversely, using too little RAM can impede the speed of a pipeline run.
    # - It is recommended that you set this to a value that when multiplied by
    #   'Number of Participants to Run Simultaneously' is as much RAM you can safely allocate.
    maximum_memory_per_participant: 3

  working_directory:

    # Deletes the contents of the Working Directory after running.
    # This saves disk space, but any additional preprocessing or analysis will have to be completely re-run.
    remove_working_dir: Off

  Amazon-AWS:

    # Enable server-side 256-AES encryption on data to the S3 bucket
    s3_encryption: On

segmentation:
  tissue_segmentation:
    Template_Based:

      # These masks should be in the same space of your registration template, e.g. if
      # you choose 'EPI Template' , below tissue masks should also be EPI template tissue masks.
      #
      # Options: ['T1_Template', 'EPI_Template']
      template_for_segmentation: []

registration_workflows:
  functional_registration:
    EPI_registration:
      ANTs:

        # EPI registration configuration - synonymous with T1_registration
        # parameters under anatomical registration above
        parameters:

nuisance_corrections:
  2-nuisance_regression:

    # Select which nuisance signal corrections to apply
    Regressors:
      - Name: Regressor_1
        Bandpass:
          bottom_frequency: 0.01
          top_frequency: 0.1
        CerebrospinalFluid:
          erode_mask: On
          extraction_resolution: 2
          summary: Mean
        GlobalSignal:
          summary: Mean
        Motion:
          include_delayed: On
          include_delayed_squared: On
          include_squared: On
        PolyOrt:
          degree: 2
        aCompCor:
          extraction_resolution: 2
          summary:
            components: 5
            method: DetrendPC
          tissues:
          - WhiteMatter
          - CerebrospinalFluid
      - Name: Regressor_2
        Bandpass:
          bottom_frequency: 0.01
          top_frequency: 0.1
        CerebrospinalFluid:
          erode_mask: On
          extraction_resolution: 2
          summary: Mean
        Motion:
          include_delayed: On
          include_delayed_squared: On
          include_squared: On
        PolyOrt:
          degree: 2
        aCompCor:
          extraction_resolution: 2
          summary:
            components: 5
            method: DetrendPC
          tissues:
          - WhiteMatter
          - CerebrospinalFluid

timeseries_extraction:
  run: Off

amplitude_low_frequency_fluctuation:

  # ALFF & f/ALFF
  # Calculate Amplitude of Low Frequency Fluctuations (ALFF) and fractional ALFF (f/ALFF) for all voxels.
  run: Off

regional_homogeneity:

  # ReHo
  # Calculate Regional Homogeneity (ReHo) for all voxels.
  run: Off

voxel_mirrored_homotopic_connectivity:

  # VMHC
  # Calculate Voxel-mirrored Homotopic Connectivity (VMHC) for all voxels.
  run: Off

network_centrality:

  # Calculate Degree, Eigenvector Centrality, or Functional Connectivity Density.
  run: Off