ngs-dna-umi-panel-variants

name	ngs-dna-umi-panel-variants
description	Run or plan targeted DNA panel variant workflows that use UMIs, duplex consensus reads, molecular barcodes, low-frequency calling, target coverage, and panel-specific QC.

Prerequisite: the plugins/ngs-analysis/ plugin root (its scripts/*.py and references/*.json) is not vendored in this flat vault. Install the ngs-analysis plugin from openai/plugins at the repo root, or every python plugins/ngs-analysis/... command below fails with No such file or directory.

UMI Panel DNA Variants

Use this skill for targeted DNA panels where molecular barcodes, UMIs, duplex consensus, or low-frequency allele detection are central to the analysis. If the panel is ordinary germline calling without molecular consensus, use ngs-dna-germline-variants.

Essential Inputs

Confirm:

• panel/capture kit name and target BED
• UMI layout: inline read, index read, single UMI, duplex UMI, or unknown
• whether consensus reads have already been generated
• FASTQ/BAM input and pairing convention
• reference build and panel-specific annotation requirements
• minimum allele fraction goal and intended use: screening, research, validation, or exploratory
• positive/negative controls and expected spike-ins when available

Route

Use a lab-validated panel workflow when provided. For public-tool planning, combine FASTQ QC, UMI extraction/consensus generation, alignment, target coverage QC, and variant calling as separate audited stages.

Preflight command:

python plugins/ngs-analysis/scripts/ngs_preflight.py --pipeline dna_umi_panel_variants --emit-install-plan

For compact local checks from prepared consensus or alignment BAM/CRAM files, use the dedicated UMI panel runner:

python plugins/ngs-analysis/scripts/run_dna_umi_panel_variants.py \
  --sample-sheet umi_panel_samples.tsv \
  --reference-fasta reference.fa \
  --target-bed panel_targets.bed \
  --umi-mode duplex \
  --umi-tag RX \
  --execute

This writes the consensus/variant command plan, molecular-consensus state, low-frequency calling settings, visualization index, qc/umi_postrun_summary.{tsv,json}, qc/umi_molecular_evidence_contract.{tsv,json}, and consensus-BAM VCF outputs when the local fgbio/samtools/bcftools backend is available. The post-run summary parses consensus flagstat, target coverage, bcftools stats, and family-size/duplex files when present; missing metrics stay explicit in the notes column. The molecular evidence contract keeps the low-AF review requirements visible per sample: consensus BAM, family-size or molecule-support metrics, variant stats, hotspot review, and duplex review.

The direct runner also emits resources/resource_plan.json, resource_manifest.tsv, resource_env.sh, and resource_readiness.md. The resource check is advisory by default so custom or reduced references can still be planned; add --genome-build, --bundle-root <bundle>=<path>, and --require-resource-plan when missing registered reference bundles should block readiness.

Decision Points

• Do not trim or discard UMI bases until their layout and destination are known.
• Separate raw read depth from unique molecular depth and consensus depth.
• Track on-target rate, coverage uniformity, family size distribution, strand/duplex support, and per-target dropout.
• Low allele fraction calls require stronger artifact review than ordinary germline calls.
• Use panel-specific hotspot/blacklist rules only when their provenance is known.

Outputs

Produce:

• UMI layout and consensus strategy
• target BED/resource manifest
• raw-depth, molecular-depth, and consensus-depth QC summary
• qc/umi_postrun_summary.tsv for consensus reads, target coverage, variant counts, family size, and duplex fraction
• qc/umi_molecular_evidence_contract.tsv for low-AF evidence readiness, hotspot review, and duplex review expectations
• variant calls with allele fraction, depth, strand/duplex support, and filtering rationale
• limitations around sensitivity, panel dropout, molecule count, and non-validated interpretation