Generate the reports

timeseries and metrics

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

   mkdir $SCRATCH/fmriprep-denoise-benchmark/ 
   

2. generate_timeseries_slurm_scripts.py:

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

   usage: generate_timeseries_slurm_scripts.py [-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:

   /scratch/${USER}/fmriprep-denoise-benchmark/giga_timeseries/{DATASET_NAME}/{FMRIPREP_VERSION}/{UNIXTIME}/.slurm
   

   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.

3. slurm_meta_confounds.sh:

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

   sbatch slurm_metric/slurm_meta_confounds.sh
   

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}]
                          output_root

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