nf-core/configs: Tufts HPC Configuration

nf-core pipelines have been configured for use on the Tufts HPC clusters operated by Research Technology at Tufts University.

To use Tufts’s profile, run the pipeline with -profile tufts.

Example:

nextflow run <pipeline> -profile tufts

Users can also put the nextflow ... command into a batch script and submit the job to computing nodes using sbatch, or launch interactive jobs on computing nodes using srun. When running on allocated compute nodes this way, both the Nextflow manager process and tasks will run on the compute nodes using the local executor. It is recommended to use -profile singularity.

Example:

nextflow run <pipeline> -profile singularity

By default, the batch partition is used for job submission. Other partitions can be specified using the --partition <PARTITION NAME> argument to the run.

GPU partition

Some tools / pipeline steps require GPUs (for example, Parabricks-based workflows). On Tufts HPC, GPU jobs should run on the gpu partition.

This profile routes GPU-enabled processes to the GPU partition using a process label:

  • Processes with the label process_gpu are submitted to the gpu partition
  • GPU resources are requested via Slurm --gres=gpu:1

Example usage

If the pipeline (or your custom config) marks GPU steps with the process_gpu label, you can run normally and those steps will be scheduled on the GPU nodes:

nextflow run <pipeline> -profile tufts

If you need to override the GPU partition name:

nextflow run <pipeline> -profile tufts --gpu_partition <GPU_PARTITION_NAME>

Note: Whether GPU jobs are used depends on the pipeline and tool configuration. Many nf-core pipelines are CPU-only unless explicitly configured to run GPU-enabled tools.

Debugging (keep work/ directory)

By default, this profile enables Nextflow cleanup on successful completion, which removes intermediate files in the work/ directory to save space.

To keep the work/ directory for debugging, disable cleanup:

nextflow run <pipeline> -profile tufts --disable_cleanup true

This is useful if you need to inspect intermediate files, reproduce errors, or re-run specific steps manually.

Environment module

Before running the pipeline, you will need to load the Nextflow module by:

module purge ## Optional but recommended
module load nextflow singularity

Config file

See config file on GitHub 

//Profile config names for nf-core/configs
params {
    config_profile_description    = 'The Tufts University HPC cluster profile provided by nf-core/configs.'
    config_profile_contact        = 'Yucheng Zhang'
    config_profile_contact_github = '@zhan4429'
    config_profile_contact_email  = 'Yucheng.Zhang@tufts.edu'
    config_profile_url            = 'https://it.tufts.edu/high-performance-computing'
}

params {
    max_cpus      = 64
    memory        = 500.GB
    max_time      = 168.h
    partition     = 'batch'
    gpu_partition = 'gpu'
    gpu_gres      = '--gres=gpu:1'
    igenomes_base = '/cluster/tufts/biocontainers/datasets/igenomes/'

    // By default, remove work/ on successful completion. Disable for debugging with: --disable_cleanup true
    disable_cleanup = false
}

// Default: CPU jobs use batch partition; GPU-labeled jobs use gpu partition
process {
    resourceLimits = [
        cpus  : params.max_cpus,
        memory: params.memory,
        time  : params.max_time
    ]
    executor = 'slurm'
    queue    = params.partition

    // GPU jobs use gpu partition (e.g., Parabricks STAR)
    withLabel: 'process_gpu' {
        queue          = params.gpu_partition
        clusterOptions = params.gpu_gres
    }
}

executor {
    queueSize         = 16
    pollInterval      = '1 min'
    queueStatInterval = '5 min'
    submitRateLimit   = '10 sec'
}

// Set $NXF_SINGULARITY_CACHEDIR in your ~/.bashrc
// to stop downloading the same image for every run
singularity {
    enabled    = true
    autoMounts = true
}

// Enable the tracing feature and allow to overwrite existing trace files
trace {
    enabled   = true
    overwrite = true
}

// Enable the report feature and allow to overwrite existing report files
report {
    enabled   = true
    overwrite = true
}

// Enable the timeline feature and allow to overwrite existing timeline files
timeline {
    enabled   = true
    overwrite = true
}

// Enable the dag feature and allow to overwrite existing dag files
dag {
    enabled   = true
    overwrite = true
}

// On a successful completion of a Nextflow run, automatically delete all intermediate files stored in the work/ directory
cleanup = !params.disable_cleanup
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