Reproducing FSL's fMRI Data Analysis via Nipype: Relevance, Challenges, and Solutions

This is the MNL repository for the study Reproducing FSL's fMRI Data Analysis via Nipype: Relevance, Challenges, and Solutions.

You can also find the Google Slides tutorial here [https://drive.google.com/drive/folders/1isZCz_YIFPb6u75GOcCM814hZi7kI_gB]

Set-ups

FSL 6.0.4

We install FSL 6.0.4. on our workstation environment by exectuing the following commands as root:
curl -fsSL --retry 5 https://fsl.fmrib.ox.ac.uk/fsldownloads/fsl-6.0.4-centos6_64.tar.gz | tar -xz -C /usr/local/fsl --strip-components 1

Thereafter, make sure each/your user has the following paths defined in their .bashrc:

FSLDIR=/usr/local/fsl
. ${FSLDIR}/etc/fslconf/fsl.sh
PATH=${FSLDIR}/bin:${PATH}
export FSLDIR PATH

Docker & Nipype

Our docker container (version: 20.10.12) is based on the Neurodocker. Please install the Neurodocker first, then use it to generate a dockerfile via the following command:

neurodocker generate docker --base ubuntu:20.04 \
--pkg-manager apt \
--install vim datalad tree \
--afni version=latest \
--ants version=2.3.1 \
--convert3d version=1.0.0 \
--dcm2niix version=latest method=source \
--freesurfer version=6.0.1 \
--copy license.txt /opt/freesurfer-6.0.1 \
--fsl version=6.0.4 \
--user=neuro \
--miniconda \
create_env=neuro \
conda_install="python=3.7 graphviz jupyter jupyterlab jupyter_contrib_nbextensions matplotlib nbformat nilearn numpy pandas pytest scipy seaborn sphinx sphinxcontrib-napoleon traits" \
pip_install="nibabel atlasreader nipype=1.6.1 neurora pybids" \
activate=true > Dockerfile

In the resulting Dockerfile, we do the following edit before it is shared with the wider community:

LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/lib/" \
MATLABCMD="/opt/matlabmcr-2018a/v94/toolbox/matlab"

This dockerfile is ready to be shared with the wider community.

Finally, we add our lab specific user and group IDs to avoid file permission problems.

Insert everything after the initial chmod 777 until mkdir -p.

&& chmod 777 /opt && chmod a+s /opt \
&& addgroup # add your group ID if needed
&& adduser # add user ID if needed, one line per user
&& mkdir -p /neurodocker \

Build the container:

docker build - < Dockerfile

Download Notebooks

You can download or clone our repository via:

git clone https://github.com/medianeuroscience/nipype_repro.git

Run!

GLM

To use our three GLM notebook, please use the following docker command:

docker run -it --rm -v {data path}:/home/{user}/data -v {output path}:/home/{user}/out -v .../nipype_repro:/home/{user}/nipype_repro -p 8888:8888 medianeuro/niflow:2.0 jupyter-lab --ip=0.0.0.0 --port=8888

Comparison

To compare outcomes, please run nipype_fsl_comp.ipynb and shell_script.ipynb outside of the docker above and within a python environment where nltools is installed