# ngs-shotgun-metagenomics

This skill starts shotgun metagenomics QC, host removal, and taxonomic or functional profiling. Use it to structure an analysis from FASTQ files.

- skill · `type=skill` · Codex, ChatGPT · 3 installs · ★ 7604
- Author: OpenAI · official OpenAI repository
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/openai/plugins/tree/HEAD/plugins/ngs-analysis/skills/ngs-shotgun-metagenomics/SKILL.md
- Updated: 2026-10-08
- HTML: https://affpapa.org/en/nevibecode/skills/ngs-shotgun-metagenomics

## What it does

The skill starts a shotgun metagenomics workflow from FASTQ data. It checks paired-end or single-end reads, sample metadata, batches, and controls, then can run `seqkit stats`, `FastQC`, and `MultiQC`. For profiling, it supports `nf-core/taxprofiler`, `Kraken2`, `Bracken`, `MetaPhlAn`, and `HUMAnN`, with native tables, summaries, SVG plots, and HTML dashboards when the relevant outputs exist.

Its scripts include `ngs_preflight.py`, `run_fastq_assay_package.py`, `run_shotgun_metagenomics.py`, and `run_nfcore_pipeline.py`. Supplying `--host-reference` adds a `KneadData` host-depletion step; cleaned reads go into `host_depletion/` before downstream Kraken2 and HUMAnN runs. Database bundles are required for the matching profiling steps, and large databases need approval for their size and destination before download. Negative controls remain visible during QC and review.

## Install

### Codex (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add openai/plugins --skill ngs-shotgun-metagenomics -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/ngs-shotgun-metagenomics/SKILL.md` — For all projects use ~/.agents/skills/

### Claude Code

1. **Skills CLI (Vercel)**
```bash
npx skills add openai/plugins --skill ngs-shotgun-metagenomics -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/ngs-shotgun-metagenomics/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/ngs-shotgun-metagenomics/

### Cursor

**Manually: put the files in place**
- File: `.cursor/skills/ngs-shotgun-metagenomics/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install openai/plugins ngs-shotgun-metagenomics
```

2. **Manually: put the files in place**
- File: `.github/skills/ngs-shotgun-metagenomics/SKILL.md`

### Gemini CLI

**Platform CLI**
```bash
gemini skills install https://github.com/openai/plugins --path plugins/ngs-analysis/skills/ngs-shotgun-metagenomics
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/ngs-shotgun-metagenomics/SKILL.md` — The legacy .windsurf/skills/ path still works

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/openai/plugins/tree/HEAD/plugins/ngs-analysis/skills/ngs-shotgun-metagenomics/SKILL.md

## When to use it
- validate shotgun FASTQ inputs
- remove host reads with KneadData
- build taxonomic tables with Kraken2 and Bracken
- produce HUMAnN pathway and gene-family profiles
- create review dashboards from profiling matrices

## Example prompts
- Inspect `shotgun_samples.csv`, run the FASTQ QC checks, and prepare the execution plan.
- Run taxonomic and functional profiling with `/db/kraken2/standard`, `/db/humann`, and `sample_metadata.tsv`.
- Use the `nf-core/taxprofiler` test run and place its results in `results/taxprofiler_test`.

## Source text · SKILL.md · MIT

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BEGIN THIRD-PARTY FILE 1d82cd7454f58c17
````text
---
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.
---

# 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`
````
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