module load singularity-fmriprep
fmriprep is installed as a singularity container. By default it will always run the current latest version. If you need a version that is not currently installed on triton, please open an issue at https://version.aalto.fi/gitlab/AaltoScienceIT/triton/issues
Here an example to run fmriprep for one subject, using an interactive session, without free-surfer reconall, using ica-aroma. The raw data in BIDS format are in the path
<path-to-bids>, then you can create a folder for the derivatives that is different than the BIDS folder
<path-to-your-derivatives-folder>. Also create a temporary folder under your scratch/work folders for storing temporary files
<path-to-your-scratch-temporary-folder> for example
/scratch/work/USERNAME/tmp/. The content of this folder is removed after fmriprep has finished.
# Example running in an interactive session ssh triton.aalto.fi sinteractive --time=24:00:00 --mem=20G # you might need more memory or time depending on the size module load singularity-fmriprep singularity_wrapper exec fmriprep <path-to-bids> <path-to-your-derivatives-folder> -w <path-to-your-scratch-temporary-folder> participant --participant-label 01 --use-aroma --fs-no-reconall --fs-license-file /scratch/shareddata/set1/freesurfer/license.txt
This might give the exit error “OSError: handle is closed”, this is a python thing, see https://neurostars.org/t/fmriprep-error-oserror-handle-is-closed/4030. The general rule is that if the reports are generated, then everything is done with the preprocessing.
If you want to parallelyze things you can write a script that cycles through each subject labels and queues SBATCH jobs for each subject (it can be an array job or a series of serial jobs). It is important you tune your memory and time requirements before processing many subjects at once.
Fmriprep does the minimal preprocessing. There is no smoothing, no temporal filtering and in general you need to regress out the estimated confounds. The most simple way is:
module load fsl fsl_regfilt -i $inputniifile -d "$file_with_bold_confounds.tsv" -o $outputniifile -f 1,2,3,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31
- There are also tools for post-processing such as:
These are not installed on the singularity image, hence you need to experiment with these on your own.