This guide is based off of xcpEngine's own tutorial
This a guide for running xcpEngine on Argon. xcpEngine is a tool that takes the output from fmriprep and completes a variety of analytical outputs (e.g. reho, alff, etc) as both niftis and tabular data (i.e. CSVs). The CSV data is data from a per-region/parcel basis from an atlas. xcpEngine supports several atlases, so you can get output from several atlas in one run.
The first step will be to log into argon (through a terminal)
# example ssh [email protected]
ssh <hawkid>@argon.hpc.uiowa.edu
and if you're off campus, you can use port 40
ssh <hawkid>@argon.hpc.uiowa.edu -p 40
While logged into Argon, we will be using the singularity image of xcpEngine so we can run it on Argon without having to worry about installing all the necessary software. Even though xcpEngine does not have an image on singularityhub, we can build a singularity image from xcpEngine's docker image on dockerhub.
It's better to build from a tagged version of an image (e.g. 1.0) instead of lastest because latest represents
the most current version of the image and everytime they change the image, the latest tag will now point to a different image.
If we want to be reproducible (it's all the rage these days), using the tag 1.0 should always point to the same
image across eternity and should always give us the same result.
# make a place to keep our singularity images
mkdir -p ${HOME}/simgs
# make our singularity image
singularity build ~/simgs/xcpEngine_v1.0.simg docker://pennbbl/xcpengine:1.0
To run xcpEngine, we need data, specifically data that has been processed by fmriprep. Thankfully, the developers of xcpEngine have provided an example dataset.
# url of the data
curl -o fmriprep.tar.gz -SL https://ndownloader.figshare.com/files/13598186
# untar (extract) the data
tar xvf fmriprep.tar.gz
Next, we need two files: 1) a design file that defines what steps we want to run on our data and 2) a cohort file that specifies which participants to run.
# download the design file (if necessary)
curl -O https://raw.githubusercontent.com/PennBBL/xcpEngine/master/designs/fc-36p.dsn
Here are the internals of the cohort file:
id0,img
sub-1,fmriprep/sub-1/func/sub-1_task-rest_space-T1w_desc-preproc_bold.nii.gz
All we need now is a directory to place the outputs, then we can run xcpEngine.
mkdir -p ./xcp_output
Now we are ready to run xcpEngine! I made a little script to help make a "job" file we can submit to the cluster. It requires our email address as input:
./create_job.sh [email protected]
create_job.sh should create a "job" file named sample_xcpengine.job that looks like this:
#!/bin/bash
#$ -pe smp 6
#$ -q UI
#$ -m bea
#$ -M [email protected]
#$ -e /Users/jdkent/xcpEngine/fc.err
#$ -o /Users/jdkent/xcpEngine/fc.out
singularity run -H /Users/jdkent/singularity_home \
/Users/jdkent/simgs/xcpEngine_v1.0.simg \
-d /Users/jdkent/xcpEngine/fc-36p.dsn \
-c /Users/jdkent/xcpEngine/func_cohort.csv \
-o /Users/jdkent/xcpEngine/xcp_output \
-t 1 -r /Users/jdkent/xcpEngine
and we can submit sample_xcpengine.job to the cluster using:
qsub sample_xcpengine.job
We will get an email when the job starts and finishes.
And you're done running it!
TODO: analyze the outputs