openai/ngs-analysis-router

Life Sciences NGS Analysis Router

Use this skill as the top-level entrypoint for ambiguous or broad sequencing-analysis requests.

Start Here

Inspect the available inputs before asking the user questions. Look for:

• Illumina run-folder files: RunInfo.xml, RunParameters.xml, SampleSheet.csv, Data/Intensities/BaseCalls
• FASTQs: *.fastq, *.fq, *.fastq.gz, *.fq.gz
• BAM/CRAM/VCF: *.bam, *.cram, *.vcf, *.vcf.gz
• count matrices: matrix.mtx, features.tsv, barcodes.tsv, *.h5, *.h5ad, *.rds
• metadata: sample sheets, design files, target BEDs, reference FASTA/GTF, primer files

Read references/intake-schema.json and references/pipeline-registry.json when forming the route.

Intake Rules

Ask the smallest set of missing questions needed to choose a defensible pipeline. Do not ask the full questionnaire if file inspection already answers a field.

Always resolve:

• input type
• assay type
• desired output
• organism/reference
• paired-end vs single-end when FASTQs are involved
• any assay-specific design file or metadata required for the requested result
• runtime constraints: local/HPC/cloud, container availability, and whether installs are allowed

For human data, ask whether cloud upload is allowed before suggesting BaseSpace, Terra, DNAnexus, or any cloud path.

Routing

Route to one leaf skill:

• BCL run folder or demultiplexing: ngs-bcl-to-fastq
• QC/trimming only: ngs-fastq-qc
• WGS/WES/panel variants: ngs-dna-variant-calling, then a subtype skill when the analysis model is clear
• germline WGS/WES/panel variants: ngs-dna-germline-variants
• tumor-normal or tumor-only somatic variants: ngs-dna-somatic-variants
• UMI, duplex, or low-frequency targeted panels: ngs-dna-umi-panel-variants
• bulk RNA-seq kickoff: ngs-bulk-rnaseq
• bulk RNA-seq FASTQ-to-count QC: ngs-bulk-rnaseq-counts-qc
• bulk RNA-seq differential expression from counts: ngs-bulk-rnaseq-differential-expression
• single-cell or single-nucleus FASTQ-to-matrix kickoff: ngs-scrna-seq
• single-cell or single-nucleus post-count QC/annotation/UMAP: scrna-seq-qc
• epigenomics kickoff: ngs-epigenomics-peaks
• ATAC-seq QC/peaks/accessibility: ngs-atacseq-peaks-qc
• ChIP-seq, CUT&RUN, or CUT&Tag QC/peaks: ngs-chip-cutrun-peaks-qc
• 16S/18S/ITS/COI amplicons: ngs-amplicon-microbiome
• shotgun metagenomics: ngs-shotgun-metagenomics
• runtime/package setup only: ngs-runtime-env

Prefer public, runtime-installable packages and nf-core workflows. Surface license/EULA/account boundaries before using proprietary or cloud tools.

Preflight

Before proposing installation or execution, run a preflight plan from the repo root:

python plugins/ngs-analysis/scripts/ngs_preflight.py --pipeline <pipeline_key> --emit-install-plan

When the user needs an approval-ready install handoff, write persistent install artifacts:

python plugins/ngs-analysis/scripts/ngs_preflight.py --pipeline <pipeline_key> --manager micromamba --install-plan-outdir runtime_readiness/<pipeline_key>_install

Treat install_plan.json as the canonical review artifact. install_commands.sh is generated from the same plan and stays review-only unless the user explicitly approves execution with NGS_RUN_INSTALL_COMMANDS=1.

For reference- or database-heavy pipelines, also create a resource plan before saying the workflow is runnable:

python plugins/ngs-analysis/scripts/ngs_reference_manager.py plan --pipeline <pipeline_key> --genome-build <build> --outdir resource_readiness/<pipeline_key>

Use --include-optional for shotgun, amplicon, or motif-enabled epigenomics runs when optional databases materially affect the requested output.

Use --network-checks only when the user allows network checks. Use --install-missing --yes only when the user explicitly asks to install.

Output Contract

Return:

1. the routed analysis type and confidence
2. missing essential parameters, if any
3. recommended public pipeline or package family
4. local tool preflight summary
5. preflight-first command or next concrete action
6. caveats around licenses, cloud upload, database size, and reference data