viral-ngs: Skill for Claude Code

Running Batch Jobs on GCP via dsub

Use dsub to run one-off compute jobs on Google Cloud when your analysis requires more compute/memory than the local environment, or needs specific Docker images that are impractical to run locally.

When to Use

• Analysis tools need >8GB RAM (e.g., VADR, BLAST, assembly)
• Need to run many independent jobs in parallel (batch processing)
• Need a specific Docker image with pre-installed tools
• Data lives in GCS and is most efficiently processed in-cloud

Prerequisites

• dsub installed (ask the user where their dsub installation or venv is located)
• gcloud CLI authenticated with a GCP project that has Batch API enabled
• GCS bucket accessible by the project's default service account

Generic Invocation

dsub --provider google-cls-v2 \
  --project <gcp-project> \
  --regions <region> \
  --image <docker-image> \
  --machine-type <machine-type> \
  --script <script.sh> \
  --tasks <tasks.tsv> \
  --logging gs://<bucket>/logs/<job-name>/

Key Parameters

Parameter	Description
--provider google-cls-v2	Use Google Cloud Batch (recommended over Life Sciences)
--project	GCP project with Batch API enabled
--regions	Compute region (e.g., us-central1)
--image	Docker image to run (e.g., staphb/vadr:1.6.4)
--machine-type	VM type (e.g., n1-highmem-4 for 26GB RAM)
--script	Local shell script to execute inside the container
--tasks	TSV file defining one row per job (batch mode)
--logging	GCS path for stdout/stderr logs

Task TSV Format

The tasks TSV defines inputs, outputs, and environment variables for each job. Header row uses column prefixes to declare types:

--env VAR1	--env VAR2	--input FASTA	--output RESULT	--output LOG
value1	value2	gs://bucket/input.fasta	gs://bucket/output.txt	gs://bucket/log.txt

• --env NAME -- environment variable passed to the script
• --input NAME -- GCS file downloaded to a local path; the env var is set to the local path
• --output NAME -- local path; after the script finishes, the file is uploaded to GCS