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Running MRIQC

Tip

Try MRIQC online on OpenNeuro - without installation!

MRIQC is a BIDS-App [BIDSApps], and therefore it inherently understands the :abbr:`BIDS (brain imaging data structure)` standard [BIDS] and follows the BIDS-Apps standard command line interface:

mriqc bids-root/ output-folder/ participant

That simple command runs MRIQC on all the T1w and BOLD images found under the BIDS-compliant folder bids-root/. The last participant keyword indicates that the first level analysis is run. (i.e. extracting the :abbr:`IQMs (image quality metrics)` from the images retrieved within bids-root/). The second level (group) is automatically run if no particular subject is provided for analysis.

Note

If the argument --participant-label is not provided, then all subjects will be processed and the group level analysis will automatically be executed without need of running the command in item 3.

To specify one particular subject, the --participant-label argument can be used:

mriqc bids-root/ output-folder/ participant --participant-label S01 S02 S03

That command will run MRIQC only on the subjects indicated: only bids-root/sub-S01, bids-root/sub-S02, and bids-root/sub-S03 will be processed. In this case, the group level will not be triggered automatically. We generate the group level results (the group level report and the features CSV table) with:

mriqc bids-root/ output-folder/ group

Examples of the generated visual reports are found in :ref:`The MRIQC Reports <reports>`.

Warning

MRIQC by default attempts to upload anonymized quality metrics to a publicly accessible web server (mriqc.nimh.nih.gov). The uploaded data consists only of calculated quality metrics and scanning parameters. It removes all personal health information and participant identifiers. We try to collect this data to build normal distributions for improved outlier detection, but if you do not wish to participate you can disable the submission with the --no-sub flag.

BIDS data organization

The software automatically finds the data the input folder if it follows the :abbr:`BIDS (brain imaging data structure)` standard [BIDS]. A fast and easy way to check that your dataset fulfills the :abbr:`BIDS (brain imaging data structure)` standard is the BIDS validator.

BIDS-App levels

In the participant level, all individual images to be processed are run through the pipeline, and the :ref:`MRIQC measures <measures>` are extracted and the individual reports (see :ref:`The MRIQC Reports <reports>`) generated. In the group level, the :abbr:`IQMs (image quality metrics)` extracted in first place are combined in a table and the group reports are generated.

Command line interface

.. argparse::
   :ref: mriqc.cli.parser._build_parser
   :prog: mriqc
   :nodefault:
   :nodefaultconst:

Running mriqc on HPC clusters

Singularity containers

Requesting resources

We have profiled cores and memory usages with the resource profiler tool of nipype.

An MRIQC run of one subject (from the ABIDE) dataset, containing only one run, one BOLD task (resting-state) yielded the following report:

Using the MultiProc plugin of nipype with nprocs=10, the workflow nodes run across the available processors for 41.68 minutes. A memory peak of 8GB is reached by the end of the runtime, when the plotting nodes are fired up.

We also profiled MRIQC on a dataset with 8 tasks (one run per task), on ds030 of OpenfMRI:

Again, we used n_procs=10. The software run for roughly about the same time (47.11 min). Most of the run time, memory usage keeps around a maximum of 10GB. Since we saw a memory consumption of 1-2GB during the the 1-task example, a rule of thumb may be that each task takes around 1GB of memory.