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create new config bih for use with the BIH HPC cluster
Co-authored-by: Shuba Alampalli <[email protected]>
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@@ -44,6 +44,7 @@ jobs: | |
- "azurebatch" | ||
- "bi" | ||
- "bigpurple" | ||
- "bih_hpc" | ||
- "binac" | ||
- "biohpc_gen" | ||
- "biowulf" | ||
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params { | ||
config_profile_name = 'bih' | ||
config_profile_description = 'Berlin Institute of Health HPC cluster profile provided by nf-core/configs.' | ||
config_profile_contact = 'BIH-HPC IT Team <[email protected]>' | ||
config_profile_url = 'https://www.hpc.bihealth.org/' | ||
max_memory = 340.GB | ||
max_cpus = 64 | ||
max_time = 7.d | ||
} | ||
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process { | ||
executor = 'slurm' | ||
maxRetries = 2 | ||
clusterOptions = "--export=ALL" | ||
} | ||
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apptainer { | ||
enabled = true | ||
autoMounts = true | ||
cacheDir = "$params.scratch/apptainer_img_$USER" | ||
} | ||
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cleanup = true | ||
workDir = "$params.scratch/work_$USER" | ||
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profiles { | ||
debug { | ||
cleanup = false | ||
} | ||
} |
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# nf-core/configs: BIH HPC Configuration | ||
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This configuration enables the use of nf-core pipelines on the [BIH HPC cluster at the Berlin Institute of Health operated by CUBI]([https://www.hpc.bihealth.org/]). | ||
To use, run a pipeline with `-profile bih`. | ||
This will download and launch the [`bih.config`](../conf/bih.config) which has been pre-configured with a setup suitable for the BIH HPC cluster. | ||
It will use slurm as a scheduler for the compute cluster, defines max resources, and specifies cache locations for apptainer. | ||
Pipeline specific parameters still need to be configured manually. | ||
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### Install Nextflow and nf-core | ||
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The latest version of Nextflow is not installed by default on the BIH HPC cluster. | ||
You can install it via conda following the [official documentation](https://nf-co.re/docs/usage/getting_started/installation#bioconda-installation): | ||
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``` | ||
# Install Bioconda according to the documentation, notably setting up channels and disabling auto-activation of the base environment. | ||
conda config --add channels defaults | ||
conda config --add channels bioconda | ||
conda config --add channels conda-forge | ||
conda config --set auto_activate_base false | ||
# Create the environment env_nf, and install the tool nextflow as well as nf-core. | ||
conda create --name env_nf nextflow nf-core | ||
``` | ||
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### Run Nextflow | ||
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Here is an example of an sbatch script with the nf-core pipeline rnaseq ([read documentation here](https://nf-co.re/rnaseq/3.14.0)). | ||
The user has to include a scratch path and the parameters of the pipeline. | ||
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``` | ||
# Initiating SLURM options | ||
#!/bin/bash | ||
#SBATCH --job-name=rnaseq_nf | ||
#SBATCH --mem-per-cpu=10G | ||
#SBATCH --ntasks=1 | ||
#SBATCH -n 1 | ||
#SBATCH --output=%x_%A_%a.log | ||
# Launch conda and nextflow/nf-core | ||
source <path to your conda installation>/etc/profile.d/conda.sh | ||
conda activate env_nf | ||
# Nextflow run | ||
nextflow run nf-core/rnaseq -r 3.14.0 -profile bih,test,apptainer \ | ||
--scratch "<path to your scratch folder>" \ | ||
--outdir "test_run_rnaseq" | ||
``` | ||
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All of the intermediate files required to run the pipeline will be stored in the `<path to your scratch folder>/work_$USER/` directory and the docker/apptainer images in the `<path to your scratch folder>/apptainer_imgs_$USER/`. | ||
Therefore, we recommend the `--scratch` option to point to a user/group/project's scratch directory. | ||
If the pipeline runs successfully, files in the work directory are deleted automatically. | ||
If the pipeline exits with an error, the work directory is not deleted and pipeline execution can be continued with the `-resume` option. | ||
Main output files created by the pipeline will be saved in the `--outdir` directory. | ||
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