Important
You will need an account to use the HPC cluster to run the pipeline.
Regarding environment variables in ~/.bashrc
, make sure you have a setup similar to the one below. If you're already part of a VO, ask for one or use VSC_DATA_USER
instead of VSC_DATA_VO_USER
.
# Needed for Tier1 accounts, not for Tier2
export SLURM_ACCOUNT={FILL_IN_NAME_OF_YOUR_ACCOUNT}
export SALLOC_ACCOUNT=$SLURM_ACCOUNT
export SBATCH_ACCOUNT=$SLURM_ACCOUNT
# Needed for running Nextflow jobs
export NXF_HOME=$VSC_DATA_VO_USER/.nextflow
# Needed for running Apptainer containers
export APPTAINER_CACHEDIR=$VSC_DATA_VO_USER/.apptainer/cache
export APPTAINER_TMPDIR=$VSC_DATA_VO_USER/.apptainer/tmp
First you should go to the cluster you want to run the pipeline on. You can check what clusters have the most free space on this link. Use the following commands to easily switch between clusters:
module purge
module swap cluster/<CLUSTER>
Before running the pipeline you will need to create a PBS script to submit as a job.
#!/bin/bash
module load Nextflow
nextflow run <pipeline> -profile vsc_ugent <Add your other parameters>
All of the intermediate files required to run the pipeline will be stored in the work/
directory. It is recommended to delete this directory after the pipeline has finished successfully because it can get quite large, and all of the main output files will be saved in the results/
directory anyway.
The config contains a cleanup
command that removes the work/
directory automatically once the pipeline has completed successfully. If the run does not complete successfully then the work/
dir should be removed manually to save storage space.
You can also add several TORQUE options to the PBS script. More about this on this link.
To submit your job to the cluster by using the following command:
qsub <script name>.pbs
Note
The profile only works for the clusters shinx
, skitty
, kirlia
, doduo
and all tier1 clusters.
Note
The default directory where the work/
and singularity/
(cache directory for images) is located in $VSC_SCRATCH_VO_USER
(when you are part of a VO) or $VSC_SCRATCH
(when you are not part of a VO) for tier2 clusters and $VSC_SCRATCH_PROJECTS_BASE/<tier1_project_name>
for tier1 clusters.
The VSC does not support Apptainer containers provided via a URL (e.g., shub://... or docker://...). One solution is to download all the containers beforehand, like in this pipeline.
First get the containers.json file from the pipeline you want to run:
nextflow inspect main.nf -profile vsc_ugent > containers.json
Then run a build script (script appended below) to build all the containers. This can take a long time and a lot of space, but it is a one-time cost. For many large images, consider running this as a job.
bash build_all_containers.sh containers.json
build_all_containers.sh
#!/bin/env bash
# avoid that Apptainer uses $HOME/.cache
export APPTAINER_CACHEDIR=/tmp/$USER/apptainer/cache
# instruct Apptainer to use temp dir on local filessytem
export APPTAINER_TMPDIR=/tmp/$USER/apptainer/tmpdir
# specified temp dir must exist, so create it
mkdir -p $APPTAINER_TMPDIR
# pull all containers from the given JSON file
# usage: build_all_containers.sh containers.json [FORCE]
JSON=$1
FORCE=${2:-false}
echo "Building containers from $JSON"
NAMES=$(sed -nE 's/.*"name": "([^"]*)".*/\1/p' $JSON)
CONTAINERS=$(sed -nE 's/.*"container": "([^"]*)".*/\1/p' $JSON)
# default FORCE to false
# paste name and containers together
paste <(echo "$NAMES") <(echo "$CONTAINERS") | while IFS=$'\t' read -r name container; do
# is sif already present, continue unless FORCE is true
if [ -f "$name.sif" ] && [ "$FORCE" != "true" ]; then
continue
fi
# if container is null, skip
if [ -z "$container" ]; then
continue
fi
# if not docker://, add docker://
if [[ $container != docker://* ]]; then
container="docker://$container"
fi
echo "Building $container"
# overwrite the existing container
apptainer build --fakeroot /tmp/$USER/$name.sif $container
mv /tmp/$USER/$name.sif $name.sif
done
Overwrite the container in your nextflow.config
. If you need GPU support, also apply the label 'use_gpu':
process {
withName: DEEPCELL_MESMER {
label = 'use_gpu'
// container "docker.io/vanvalenlab/deepcell-applications:0.4.1"
container = "./DEEPCELL_MESMER_GPU.sif"
}
}