Generate the reports#

timeseries and metrics#

  1. Create a symbolic link of the metrics to the inputs/ directory

    mkdir $SCRATCH/fmriprep-denoise-benchmark/ 

    Extract time series with different atlases. The scripts generates slurm to extract time series with different atlases. Here’s the docs.

    usage: [-h]
                                                [--slurm-account SLURM_ACCOUNT]
                                                scratch_path fmriprep_output
                                                participants_tsv virtualenv
    create timeseries extraction scripts
    positional arguments:
    scratch_path          Path to scratch space.
    fmriprep_output       Path to fMRIPrep output directory.
    participants_tsv      Path to participants.tsv in the original BIDS dataset.
    virtualenv            Path to virtual environment of this project.
    optional arguments:
    -h, --help            show this help message and exit
    --slurm-account SLURM_ACCOUNT
                            SLURM account for job submission (default: rrg-pbellec)

    We created two separate scripts for discrete and probability atlas due to different memory requirement. You will find the output under:


    Similar to fmriprep-slurm, it will give you the exact commands you need to run. It should be something looking like this:

    find /scratch/${USER}/ds000228/UNIXTIME/.slurm/smriprep_sub-*.sh -type f | while read file; do sbatch "$file"; done

    This process will take a few hours.


    Create files to determine which subject will enter the next stage for metric generation.

    sbatch slurm_metric/
  4. generate_metrics/*/slurm/metrics*.sh:

    Calculate metrics on denoising quality per atlas. Use this line to submit all jobs at once.

    find scripts/generate_metrics/slurm/metrics*.sh -type f | while read file; do sbatch $file; done

    The extra scripts in generate_metrics/ are for running directly on a computing node.

Build the book#

To improve build time, we need to summarise the metrics further. If you generated the data from scratch, you will need to run the following command.

usage: summarise_metadata [-h]
                          [--fmriprep_version {fmriprep-20.2.1lts,fmriprep-20.2.5lts}]
                          [--dataset_name {ds000228,ds000030}]
                          [--qc {stringent,minimal,None}]

Summarise denoising metrics for visualization and save at the top level of the denoise metric outputs directory.

positional arguments:
  output_root           Output root path data.

optional arguments:
  -h, --help            show this help message and exit
  --fmriprep_version {fmriprep-20.2.1lts,fmriprep-20.2.5lts}
                        Path to a fmriprep dataset.
  --dataset_name {ds000228,ds000030}
                        Dataset name.
  --qc {stringent,minimal,None}
                        Automatic motion QC thresholds.

Now you can build the book:

make book