Installation¶
There are four ways to use fmriprep: on the free cloud service OpenNeuro.org, in a Docker Container, in a Singularity Container, or in a Manually Prepared Environment. Using OpenNeuro or a local container method is highly recommended. Once you are ready to run fmriprep, see Usage for details.
OpenNeuro¶
fmriprep is available on the free cloud platform OpenNeuro.org. After uploading your BIDS-compatible dataset to OpenNeuro you will be able to run fmriprep for free using OpenNeuro servers. This is the easiest way to run fmriprep, as there is no installation required.
Docker Container¶
In order to run fmriprep in a Docker container, Docker must be installed. Once Docker is installed, the recommended way to run fmriprep is to use the fmriprep-docker wrapper, which requires Python and an Internet connection.
To install:
$ pip install --user --upgrade fmriprep-docker
When run, fmriprep-docker
will generate a Docker command line for you,
print it out for reporting purposes, and then run the command, e.g.:
$ fmriprep-docker /path/to/data/dir /path/to/output/dir participant
RUNNING: docker run --rm -it -v /path/to/data/dir:/data:ro \
-v /path/to_output/dir:/out poldracklab/fmriprep:1.0.0 \
/data /out participant
...
You may also invoke docker
directly:
$ docker run -ti --rm \
-v filepath/to/data/dir:/data:ro \
-v filepath/to/output/dir:/out \
poldracklab/fmriprep:latest \
/data /out/out \
participant
For example:
$ docker run -ti --rm \
-v $HOME/fullds005:/data:ro \
-v $HOME/dockerout:/out \
poldracklab/fmriprep:latest \
/data /out/out \
participant \
--ignore fieldmaps
See External Dependencies for more information (e.g., specific versions) on what is included in the latest Docker images.
Singularity Container¶
For security reasons, many HPCs (e.g., TACC) do not allow Docker containers, but do allow Singularity containers. In this case, start with a machine (e.g., your personal computer) with Docker installed. Use docker2singularity to create a singularity image. You will need an active internet connection and some time.
$ docker run --privileged -t --rm \
-v /var/run/docker.sock:/var/run/docker.sock \
-v D:\host\path\where\to\output\singularity\image:/output \
singularityware/docker2singularity \
poldracklab/fmriprep:latest
Beware of the back slashes, expected for Windows systems. For *nix users the command translates as follows:
$ docker run --privileged -t --rm \
-v /var/run/docker.sock:/var/run/docker.sock \
-v /absolute/path/to/output/folder:/output \
singularityware/docker2singularity \
poldracklab/fmriprep:latest
Transfer the resulting Singularity image to the HPC, for example, using scp
.
$ scp poldracklab_fmriprep_latest-*.img user@hcpserver.edu:/path/to/downloads
If the data to be preprocessed is also on the HPC, you are ready to run fmriprep.
$ singularity run path/to/singularity/image.img \
path/to/data/dir path/to/output/dir \
participant \
--participant-label label
For example:
$ singularity run ~/poldracklab_fmriprep_latest-2016-12-04-5b74ad9a4c4d.img \
/work/04168/asdf/lonestar/ $WORK/lonestar/output \
participant \
--participant-label 387 --nthreads 16 -w $WORK/lonestar/work \
--omp-nthreads 16
Note
Singularity by default exposes all environment variables from the host inside the container. Because of this your host libraries (such as nipype) could be accidentally used instead of the ones inside the container - if they are included in PYTHONPATH. To avoid such situation we recommend unsetting PYTHONPATH in production use. For example:
$ PYTHONPATH="" singularity run ~/poldracklab_fmriprep_latest-2016-12-04-5b74ad9a4c4d.img \
/work/04168/asdf/lonestar/ $WORK/lonestar/output \
participant \
--participant-label 387 --nthreads 16 -w $WORK/lonestar/work \
--omp-nthreads 16
Manually Prepared Environment¶
Note
This method is not recommended! Make sure you would rather do this than use a Docker Container or a Singularity Container.
Make sure all of fmriprep’s External Dependencies are installed.
These tools must be installed and their binaries available in the
system’s $PATH
.
In particular, FreeSurfer requires a license file (see The FreeSurfer license).
If you have pip installed, install fmriprep
$ pip install fmriprep
If you have your data on hand, you are ready to run fmriprep:
$ fmriprep data/dir output/dir participant --participant-label label
The FreeSurfer license¶
FMRIPREP uses FreeSurfer tools, which require a license to run.
To obtain a FreeSurfer license, simply register for free at https://surfer.nmr.mgh.harvard.edu/registration.html.
When using manually-prepared environments, FreeSurfer will search for a license key
file first using the $FS_LICENSE
environment variable and then in the default
path to the license key file ($FREESURFER_HOME/license.txt
).
It is possible to run the docker container pointing the image to a local path
where a valid license file is stored.
For example, if the license is stored in the $HOME/.licenses/freesurfer/license.txt
file on the host system:
$ docker run -ti --rm \
-v $HOME/fullds005:/data:ro \
-v $HOME/dockerout:/out \
-v $HOME/.licenses/freesurfer/license.txt:/opt/freesurfer/license.txt \
poldracklab/fmriprep:latest \
/data /out/out \
participant \
--ignore fieldmaps
Using FreeSurfer can also be enabled when using fmriprep-docker
:
$ fmriprep-docker --fs-license-file $HOME/.licenses/freesurfer/license.txt \
/path/to/data/dir /path/to/output/dir participant
RUNNING: docker run --rm -it -v /path/to/data/dir:/data:ro \
-v /home/user/.licenses/freesurfer/license.txt:/opt/freesurfer/license.txt \
-v /path/to_output/dir:/out poldracklab/fmriprep:1.0.0 \
/data /out participant
...
If the environment variable $FS_LICENSE
is set in the host system, then
it will automatically used by fmriprep-docker
. For instance, the following
would be equivalent to the latest example:
$ export FS_LICENSE=$HOME/.licenses/freesurfer/license.txt
$ fmriprep-docker /path/to/data/dir /path/to/output/dir participant
RUNNING: docker run --rm -it -v /path/to/data/dir:/data:ro \
-v /home/user/.licenses/freesurfer/license.txt:/opt/freesurfer/license.txt \
-v /path/to_output/dir:/out poldracklab/fmriprep:1.0.0 \
/data /out participant
...