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Skillsparabricks

parabricks

Data & analytics

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Updated 10-16 02:34

About this skill

Parabricks

Purpose

Use this skill to discover the right NVIDIA Parabricks pbrun command, assess runtime readiness, and generate version-aware command guidance for individual tools and pipelines.

Do not use this skill for whole-workflow inspection, acceleration planning, or wiring optional GPU branches. For pipeline-level work, use genomics-workflow-acceleration.

When to Use This Skill

  • Which pbrun tool fits the user's data and goal
  • GPU, driver, Docker, container, storage, or installation readiness
  • Command shape, flags, and validation for a specific Parabricks tool
  • Troubleshooting a single Parabricks command or tool family

Prerequisites

Ask for input data type, sequencing technology, reference build, sample structure, desired output, target Parabricks version/container tag, and runtime target before recommending commands.

If the user is unsure which tool applies, read tool-index.md first, then load the matching references/pbrun-<tool>.md file.

Limitations

This skill routes and guides Parabricks commands. It does not install Parabricks, infer missing sample metadata, guarantee output parity, provide clinical interpretation, or promise exact runtime without benchmark data.

Workflow

  1. Confirm the Parabricks version or container tag. Verify the current NVIDIA docs when the user asks for the latest tool list or version-sensitive flags.
  2. Classify the request:
  3. Collect missing biological and filesystem context before generating commands.
  4. Generate conservative Docker commands with explicit mounts, workdir, and placeholders. Validate paths, indexes, and outputs after command generation.

Tool Reference Index

Load only the reference file for the selected tool.

Tool Reference Use when
applybqsr pbrun-applybqsr.md Apply BQSR table to aligned BAM
bam2fq pbrun-bam2fq.md BAM → FASTQ conversion
bamsort pbrun-bamsort.md Standalone BAM sort
bqsr pbrun-bqsr.md Generate BQSR recalibration table
fq2bam pbrun-fq2bam.md Short-read DNA paired FASTQ → BAM/CRAM
fq2bam_meth pbrun-fq2bam_meth.md Bisulfite/methylation FASTQ → BAM/CRAM
giraffe pbrun-giraffe.md Pangenome graph alignment
markdup pbrun-markdup.md Standalone duplicate marking
minimap2 pbrun-minimap2.md Long-read FASTQ alignment
rna_fq2bam pbrun-rna_fq2bam.md RNA-seq FASTQ(s) → splice-aware BAM (STAR alignment)
starfusion pbrun-starfusion.md Fusion detection from chimeric junction input + STAR-Fusion genome library
germline pbrun-germline.md GATK-style germline pipeline from FASTQ
deepvariant_germline pbrun-deepvariant_germline.md DeepVariant germline pipeline from FASTQ
haplotypecaller pbrun-haplotypecaller.md Standalone HaplotypeCaller from BAM/CRAM
deepvariant pbrun-deepvariant.md Standalone DeepVariant from BAM/CRAM
somatic pbrun-somatic.md Tumor-normal somatic pipeline
mutectcaller pbrun-mutectcaller.md Mutect2-compatible somatic calling
deepsomatic pbrun-deepsomatic.md DeepSomatic-based somatic calling
pacbio_germline pbrun-pacbio_germline.md PacBio long-read germline
ont_germline pbrun-ont_germline.md Oxford Nanopore long-read germline
pangenome_germline pbrun-pangenome_germline.md Pangenome-aware germline
pangenome_aware_deepvariant pbrun-pangenome_aware_deepvariant.md Pangenome-aware DeepVariant
prepon pbrun-prepon.md Pangenome-aware preprocessing
postpon pbrun-postpon.md Pangenome-aware post-processing
bammetrics pbrun-bammetrics.md Whole-genome coverage/depth metrics
collectmultiplemetrics pbrun-collectmultiplemetrics.md Multiple Picard/GATK-style alignment metrics
genotypegvcf pbrun-genotypegvcf.md Joint-genotype GVCF input(s) into VCF
indexgvcf pbrun-indexgvcf.md Index GVCF input
dbsnp pbrun-dbsnp.md dbSNP annotation on variant files

For routing heuristics when multiple tools could apply, see tool-index.md.

Runtime Readiness

For GPU, driver, Docker, container, storage, or installation questions, read runtime-environment.md and prefer:

python3 skills/parabricks/scripts/check_parabricks_runtime.py

Add --path <dir> for known input/output/tmp paths. Run container probes only with user consent.

Command Shape

docker run --rm --gpus all \
  --volume /host/input:/workdir \
  --volume /host/output:/outputdir \
  --workdir /workdir \
  nvcr.io/nvidia/clara/clara-parabricks:<version> \
  pbrun <selected-tool> \
  <tool-specific-options>

Check the version-specific tool reference before finalizing flags.

Troubleshooting

Error Cause Solution
Multiple plausible tools Data type or goal underspecified Ask for assay, inputs, caller preference, desired output; use tool-index
Exact flag requested Options are version-sensitive Check the selected tool reference and NVIDIA docs
Runtime question GPU, Docker, drivers, or storage Use runtime-environment reference and diagnostic script
Wrong tool family Assay or input type unclear Confirm DNA/RNA/methylation/long-read/pangenome before routing
CUDA or memory failure Runtime not ready or GPU memory constrained Assess runtime before tuning command flags

Guardrails

  • Treat command availability and options as version-sensitive.
  • Do not infer exact flags from command names alone.
  • Do not collapse standalone tools and full pipelines when explaining tradeoffs.
  • Do not substitute DNA fq2bam for RNA, or germline for somatic callers.
  • Do not invent sample names, read groups, reference builds, known-sites files, model files, graph resources, container tags, or output paths.
  • Do not install, upgrade, or modify packages. Label setup commands as user-run.
  • Do not claim CPU execution of Parabricks tools.
  • Do not claim biological or VCF parity without a comparison run.
  • Prefer official NVIDIA docs for exact command syntax and option defaults.

Key References