Kick off public shotgun metagenomics QC, host-depletion, taxonomic profiling, and functional profiling workflows using nf-core/taxprofiler, Kraken2, Bracken, MetaPhlAn, and HUMAnN.
Scanned 9/12/2026
Install to Claude Code
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---
name: ngs-shotgun-metagenomics
description: Kick off public shotgun metagenomics QC, host-depletion, taxonomic profiling, and functional profiling workflows using nf-core/taxprofiler, Kraken2, Bracken, MetaPhlAn, and HUMAnN.
---
> 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`.
# Shotgun Metagenomics
Use this skill for shotgun metagenomic FASTQs.
## Essential Inputs
Confirm:
- paired-end or single-end reads
- host organism and host-depletion requirement
- target outputs: taxonomic profile, functional profile, assembly, binning, or QC only
- preferred database family, if any
- database paths or permission to download large databases
- sample metadata, batches, and negative controls
## Public Defaults
Prefer `nf-core/taxprofiler` for reproducible taxonomic profiling. Use direct Kraken2/Bracken, MetaPhlAn, or HUMAnN when the user wants a focused path or already has databases installed.
For direct backend execution, prefer the plugin runner over handwritten shell when possible because it validates database bundle contents and records `resources/resource_plan.json`, `resource_manifest.tsv`, `resource_env.sh`, and `resource_readiness.md`. `--run-bracken` and `--run-humann` make those database bundles blocking, not merely optional.
## Preflight
```bash
python plugins/ngs-analysis/scripts/ngs_preflight.py --pipeline shotgun_metagenomics --emit-install-plan
```
## Local Execution Package
For FASTQ intake/QC before host-depletion, taxonomic profiling, or functional profiling, use:
```bash
python plugins/ngs-analysis/scripts/run_fastq_assay_package.py \
--lane shotgun_metagenomics \
--sample-sheet shotgun_samples.csv \
--execute
```
This validates read paths and structure, runs seqkit stats and FastQC/MultiQC when available, and writes `taxonomic_classification_status.json`. Add `--kraken-db /path/to/db` only when a local Kraken2 database is available; otherwise the package records the database/tool blocker explicitly.
For backend taxonomic and functional profiling when databases are available, use:
```bash
python plugins/ngs-analysis/scripts/run_shotgun_metagenomics.py \
--sample-sheet shotgun_samples.csv \
--kraken-db /db/kraken2/standard \
--host-reference /refs/human_kneaddata_db \
--run-bracken \
--run-humann \
--humann-db /db/humann \
--metadata sample_metadata.tsv \
--execute
```
For nf-core execution, use `plugins/ngs-analysis/scripts/run_nfcore_pipeline.py --pipeline taxprofiler`.
When `--host-reference` is supplied, the backend runner adds a KneadData host-depletion step, requires `kneaddata` in tool preflight, writes cleaned FASTQs under `host_depletion/`, and uses those cleaned reads for downstream Kraken2 and HUMAnN steps. Keep the host reference path and host-depletion decision visible because it can change taxonomic and functional abundance conclusions.
The backend runner writes native matrix artifacts when database tools produce outputs:
- `tables/bracken_est_reads_matrix.tsv`
- `tables/bracken_relative_abundance_matrix.tsv`
- `tables/humann_pathabundance_matrix.tsv`
- `tables/humann_genefamilies_matrix.tsv`
- `tables/bracken_summary.json` and `tables/humann_summary.json`
- `tables/top_bracken_taxa.tsv`, `tables/top_humann_pathways.tsv`, `tables/top_humann_gene_families.tsv`, and `tables/metagenomics_backend_review.json` when normalized backend matrices are available
If Kraken2/Bracken/HUMAnN outputs are absent, the summaries and visualization manifest keep those layers `not_available` instead of implying taxonomic or functional interpretation succeeded.
## Kickoff Pattern
nf-core preflight run:
```bash
nextflow run nf-core/taxprofiler \
-profile test,docker \
--outdir results/taxprofiler_test
```
Direct Kraken2 skeleton:
```bash
kraken2 \
--db /path/to/kraken2_db \
--paired sample_R1.fastq.gz sample_R2.fastq.gz \
--report results/kraken2/sample.report \
--output results/kraken2/sample.kraken
```
## Visualization Outputs
The local FASTQ package always writes `visualizations/index.html` and `visualizations/visualization_manifest.json`. With only FASTQs, this is a read-QC/readiness bundle. Provide existing `--kraken-report`, `--bracken-table`, `--humann-pathabundance`, or `--humann-genefamilies` files to generate native taxonomy and functional-profile plots without requiring a Marimo notebook. For full backend runs, `run_shotgun_metagenomics.py` now also merges generated Bracken/HUMAnN outputs into plugin-native tables for the review bundle and writes `visualizations/shotgun_backend_dashboard.html` plus SVG plots for top Bracken taxa, HUMAnN pathways, and HUMAnN gene families when the corresponding matrices are present.
## Guardrails
- Do not auto-download large databases without confirming size and destination.
- Host depletion choices can change biological conclusions; document the reference and parameters.
- Negative controls should stay visible in QC and interpretation.
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