carolfrohlich / c-pac Goto Github PK

Craddock C, Sikka S, Cheung B, Khanuja R, Ghosh SS, Yan C, Li Q, Lurie D, Vogelstein J, Burns R, Colcombe S,
Mennes M, Kelly C, Di Martino A, Castellanos FX and Milham M (2013). Towards Automated Analysis of Connectomes:
The Configurable Pipeline for the Analysis of Connectomes (C-PAC). Front. Neuroinform. Conference Abstract:
Neuroinformatics 2013. doi:10.3389/conf.fninf.2013.09.00042

@ARTICLE{cpac2013,
    AUTHOR={Craddock, Cameron  and  Sikka, Sharad  and  Cheung, Brian  and  Khanuja, Ranjeet  and  Ghosh, Satrajit S
        and Yan, Chaogan  and  Li, Qingyang  and  Lurie, Daniel  and  Vogelstein, Joshua  and  Burns, Randal  and  
        Colcombe, Stanley  and  Mennes, Maarten  and  Kelly, Clare  and  Di Martino, Adriana  and  Castellanos,
        Francisco Xavier  and  Milham, Michael},  
    TITLE={Towards Automated Analysis of Connectomes: The Configurable Pipeline for the Analysis of Connectomes (C-PAC)},     
    JOURNAL={Frontiers in Neuroinformatics},
    YEAR={2013},
    NUMBER={42},
    URL={http://www.frontiersin.org/neuroinformatics/10.3389/conf.fninf.2013.09.00042/full},
    DOI={10.3389/conf.fninf.2013.09.00042},
    ISSN={1662-5196}
}

	usage: run.py [-h]
	              [--participant_label PARTICIPANT_LABEL [PARTICIPANT_LABEL ...]]
                  [--n_cpus #]
                  [--mem #]
                  [--save_working_directory]
	              bids_dir output_dir {participant,group}

	Example BIDS App entrypoint script.

	positional arguments:
	  bids_dir              The directory with the input dataset formatted
	                        according to the BIDS standard.
	  output_dir            The directory where the output files should be stored.
	                        If you are running group level analysis this folder
	                        should be prepopulated with the results of
	                        theparticipant level analysis.
	  {participant,group}   Level of the analysis that will be performed. Multiple
	                        participant level analyses can be run independently
	                        (in parallel).

	optional arguments:
	  -h, --help            show this help message and exit
	  --participant_label PARTICIPANT_LABEL [PARTICIPANT_LABEL ...]
	                        The label(s) of the participant(s) that should be
	                        analyzed. The label corresponds to
	                        sub-<participant_label> from the BIDS spec (so it does
	                        not include "sub-"). If this parameter is not provided
	                        all subjects should be analyzed. Multiple participants
	                        can be specified with a space separated list.
      --pipeline_file       Name for the pipeline configuration file to use, the path
                            must be accessible from inside the container.
                            default="/cpac_resources/default_pipeline.yaml"
      --n_cpus              Number of execution resources available for the pipeline
                            default="1"
      --mem                 Amount of RAM available to the pipeline in GB
                            default="6"
      --save_working_dir    Indicates that the working directory, which contains
                            intermediary files, should be saved. If specified, the
                            working directory will be saved in the output directory.

docker run -i --rm \
	-v /Users/filo/data/ds005:/bids_dataset \
	-v /Users/filo/outputs:/outputs \
	bids/example \
	/bids_dataset /outputs participant --participant_label 01

docker run -i --rm \
	-v /Users/filo/data/ds005:/bids_dataset \
	-v /Users/filo/outputs:/outputs \
	bids-apps/cpac:v1.0.0 \
	/bids_dataset /outputs group