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Pipeline used to take functional data from DICOMs through group-level analyses.

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func_processing

Pipeline used to take functional data from DICOMs through group-level analyses.

Entry Points

Following python setup.py install or python setup.py develop, use the following entry points to trigger help, cli.

  • func_processing : print out entrypoints below.

  • check : print help, run cli.checks, used to determine which participants have which preprocessed files.
  • ashs : trigger help of cli.ashs, for running Automated Hippocampal Subfield Segmentation.
  • reface : trigger help of cli.reface, for de/refacing participant T1w files.
  • fmriprep : trigger help of cli.fmriprep, for moving data found in dset through FreeSurfer and fMRIPrep.
  • task_subj : trigger help of cli.afni_task_subj, move task EPI output of fmriprep through extra preprocessing, deconvolution.
  • rs_subj : trigger help of cli.afni_resting_subj, move resting EPI output of fmriprep through extra preprocessing, deconvolution.
  • task_group : trigger help of cli.afni_task_group, conduct group-level task EPI analyses.
  • rs_group : trigger help of cli.afni_resting_group, conduct group-level resting EPI analyses.

Project organization

Top Level

  • dockerfiles : Dockerfile, shell script backup
  • docs : Project documentation, for ReadTheDocs, assuming sphinx is cooperative. Build instruction found in build_docs.txt.
  • func_processing : Main package

func_processing

  • cli : Contains scripts to start AFNI, ASHS, fMRIprep, FreeSurfer, refacing, and data checking workflows.
  • examples : Contains example scripts and files.
  • logs : Mainly for completed_preprocessing.tsv, other output logs written here.
  • resources : Location of modules for AFNI, ASHS, FreeSurfer, fMRIprep, and reports.
  • tests : Scripts for testing resources and workflows.
  • tools : Location for auxiliary/shell scripts. Currently contains (outdated) cron scripts
  • workflow : Manages resources, controlled by cli.

See Wiki for details and description, now a little outdated due to refactoring.

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Pipeline used to take functional data from DICOMs through group-level analyses.

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  • Python 91.1%
  • Shell 7.1%
  • R 1.6%
  • Dockerfile 0.2%