FGCZ Configuration

Configuration file to run nf-core pipelines on the cluster of the Functional Genomics Center Zurich, a research and training facility of the ETH Z├╝rich and the University of Zurich.

Note that, at present, this config has only been tested with nf-core/viralrecon, but should function similarly for other nf-core pipelines.

To use, run the pipeline with -profile fgcz. This will download and launch the profile.config which has been pre-configured with a setup suitable for the FGCZ cluster. Using this profile, a docker image containing all of the required software will be downloaded, and converted to a Singularity image before execution of the pipeline. This requires a local installation of singularity. It is easiest to submit the pipeline from a compute node. Once the image is cached, you can also submit from the login node. The config places the singularity cache in your /srv/GT/ directory for access by all projects.

Example: /usr/local/ngseq/src/nextflow/nextflow run -profile fgcz

Before running the pipeline

Load the following modules before running any nf-core pipelines.

module load Dev/Python/3.8.3
module load Dev/Python/3.8.3

Config file

See config file on GitHub

fgcz.config
params {
	config_profile_description = "FGCZ ETH/UZH"
	config_profile_contact = "natalia.zajac@fgcz.ethz.ch"
	max_memory = 500.GB
	max_cpus = 64
	max_time = 240.h
}
 
process {
	executor = "slurm"
	maxRetries = 2
}
 
executor {
	queueSize = 30
}
 
 
 
singularity {
	enabled = true
	autoMounts = true
	cacheDir = "/srv/GT/nextflow/singularity/"
}
 
fgcz.config
params {
	config_profile_description = "FGCZ ETH/UZH"
	config_profile_contact = "natalia.zajac@fgcz.ethz.ch"
	max_memory = 500.GB
	max_cpus = 64
	max_time = 240.h
}
 
process {
	executor = "slurm"
	maxRetries = 2
}
 
executor {
	queueSize = 30
}
 
 
 
singularity {
	enabled = true
	autoMounts = true
	cacheDir = "/srv/GT/nextflow/singularity/"
}