PCP Quality Assessment Protocol
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QAP BIDS Application


Extensive information can be found in the Quality Assessment Protocol webpage.


Various objective measures for MRI data quality have been proposed over the years. However, until now no software has allowed researchers to obtain all these measures in the same place with relative ease. The Quality Assessment Protocol package allows you to obtain spatial and anatomical data quality measures for your own data. Reports can optionally be generated that provide a variety of data visualizations to aid with quality assessment.

This container calculates dataset level quality assessment metrics of structural and functional MRI data when run in "participant" mode and compiles the outputs of many different participants outputs into single CSV files when run in "group" mode.


This App has the following command line arguments:

usage: run.py [-h]
              [--participant_label PARTICIPANT_LABEL [PARTICIPANT_LABEL ...]]
              [--pipeline_file PIPELINE_FILE] [--n_cpus N_CPUS] [--mem MEM]
              [--save_working_dir] [--report]
              bids_dir output_dir {participant,group}

PCP-QAP Pipeline Runner

positional arguments:
  bids_dir              The directory with the input dataset formatted
                        according to the BIDS standard.
  output_dir            The directory where the output CSV files should be
  {participant,group}   Level of the analysis that will be performed. Multiple
                        participant level analyses can be run independently
                        (in parallel) using the same output_dir. Group level
                        analysis compiles multiple participant level quality
                        metrics intogroup-level csv files.

optional arguments:
  -h, --help            show this help message and exit
                        The label of the participant 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 PIPELINE_FILE
                        Name for the pipeline configuration file to use, uses
                        a default configuration if not specified
  --n_cpus N_CPUS       Number of execution resources available for the
                        pipeline, default=1
  --mem MEM             Amount of RAM available to the pipeline in GB, default
                        = 6
  --save_working_dir    Save the contents of the working directory.
  --report              Generates pdf for graphically assessing data quality.

To run it in participant level mode (for one participant):

docker run -i --rm \
    -v /Users/filo/data/ds005:/bids_dataset \
    -v /Users/filo/outputs:/outputs \
    bids-apps/qap:v1.0.0 \
    /bids_dataset /outputs --participant_label 01 participant

To run all subjects and generate the group level analysis report:

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

Reporting errors and getting help

Please report errors on the QAP github page issue tracker. Please use the PCP google group for help using C-PAC and this application.


We currently have a publication in preparation, in the meantime please cite our poster from INCF:

Shehzad Z, Giavasis S, Li Q, Benhajali Y, Yan C, Yang Z, Milham M, Bellec P
and Craddock C (2015). The Preprocessed Connectomes Project Quality 
Assessment Protocol - a resource for measuring the quality of MRI data.. 
Front. Neurosci. Conference Abstract: Neuroinformatics 2015. doi: 

    AUTHOR={Shehzad, Zarrar  and  Giavasis, Steven  and  Li, Qingyang  and
      Benhajali, Yassine  and  Yan, Chaogan  and  Yang, Zhen  and  Milham, 
      Michael  and  Bellec, Pierre  and  Craddock, Cameron},   
    TITLE={The Preprocessed Connectomes Project Quality Assessment Protocol
     - a resource for measuring the quality of MRI data.},      
    JOURNAL={Frontiers in Neuroscience},      
    ISSN={1662-453X} ,