---
name: metagenomics-e66eda8c4b9b
description: Shotgun metagenomics workflow with host-depletion-aware QC, taxonomic profiling, functional profiling, AMR follow-up, and reproducible community output tables.
tool_type: mixed
primary_tool: Kraken2
---

# Metagenomics

## Version Compatibility

Reference examples assume:

- `fastp` 0.23+
- `kraken2` 2.1+
- `bracken` 2.8+
- `metaphlan` 4+
- `humann` 3.9+

Verify the environment first:

- CLI: `kraken2 --version`, `bracken -v`, `metaphlan --version`, `humann --version`

## Overview

Use this skill for shotgun metagenomics when the user needs:

- QC and host depletion review
- taxonomic abundance tables
- functional pathway profiles
- AMR or strain-level follow-up

## When To Use This Skill

- the data are shotgun metagenomics rather than amplicon sequencing
- the user wants species or genus abundances, function, or resistance summaries
- multiple samples need cohort-level comparison

## Quick Route

- host-associated samples: perform host depletion before interpretation
- taxonomy only: `kraken2 + bracken` is a common pragmatic route
- function only or plus taxonomy: add `humann`
- strain claims require more evidence than top-level taxonomy calls

## Progressive Disclosure

- Read [technical_reference.md](technical_reference.md) for database choice, host contamination review, and functional profiling caveats.
- Read [commands_and_thresholds.md](commands_and_thresholds.md) for command-line patterns, thresholds, and output layout.

## Expected Inputs

- paired or single-end metagenomic FASTQ
- sample metadata
- taxonomy and optional function databases

## Expected Outputs

- `results/taxonomy/bracken_species.tsv`
- `results/taxonomy/bracken_genus.tsv`
- `results/function/pathabundance.tsv`
- `results/amr/amr_summary.tsv`
- `qc/read_processing_summary.tsv`

## Starter Pattern

```bash
fastp \
  -i sample_R1.fastq.gz \
  -I sample_R2.fastq.gz \
  -o qc/sample.clean.R1.fastq.gz \
  -O qc/sample.clean.R2.fastq.gz \
  --html qc/sample.fastp.html \
  --json qc/sample.fastp.json

kraken2 \
  --db $KRAKEN_DB \
  --paired qc/sample.clean.R1.fastq.gz qc/sample.clean.R2.fastq.gz \
  --report results/taxonomy/sample.kraken.report \
  --output results/taxonomy/sample.kraken.out \
  --confidence 0.1
```

## Workflow

### 1. Run read QC and optional host depletion

At minimum, inspect read quality, adapter content, and retained reads. For host-associated samples, remove host reads before community interpretation.

### 2. Profile taxonomy

Use a k-mer or marker-based profiler. Document the database and version because abundance results depend strongly on the reference.

### 3. Refine abundance tables

Convert raw classification to species or genus abundance tables suitable for cohort comparison.

### 4. Add function or AMR when requested

Run pathway or AMR profiling only after confirming taxonomic QC and read retention are reasonable.

### 5. Export cohort-ready outputs

Save per-sample tables and merged matrices with clear metadata joins.

## Output Artifacts

```text
results/
├── taxonomy/
│   ├── sample.kraken.report
│   ├── bracken_species.tsv
│   └── bracken_genus.tsv
├── function/
│   └── pathabundance.tsv
└── amr/
    └── amr_summary.tsv
qc/
├── read_processing_summary.tsv
└── sample.fastp.html
```

## Quality Review

- retained reads after QC should be reported explicitly
- host-associated samples with large host contamination need a clear host depletion statement
- avoid over-interpreting taxa with extremely low abundance
- abundance comparisons should state whether values are relative abundance, counts, or normalized function estimates

## Anti-Patterns

- comparing outputs from different databases as if they were directly interchangeable
- making strain-level claims from genus-level evidence
- ignoring host contamination in human-associated or plant-associated samples
- mixing taxonomy-only and pathway outputs without clarifying what each table means

## Related Skills

- Microbiome Amplicon
- Pathogen Epidemiological Genomics
- Phylogenetics

## Optional Supplements

- `scikit-bio`


---
Source attribution: Runchuan-BU
Original project: https://github.com/Runchuan-BU/BioClaw
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Dave AI.

## Upstream license notice

MIT License

Copyright (c) 2026 Gabriel Moreira

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Dave AI resource metadata

Creator / publisher: Runchuan-BU
Original project: https://github.com/Runchuan-BU/BioClaw
Attribution basis: Upstream repository explicitly recorded in package mirror path

Fields of work: Data & Analytics, Education & Research
Roles: Business Intelligence Analyst, Data Scientist, Researcher
Specialties: Specialty not specified
Tools: Bracken, Fastp, Humann, Kraken2, Metaphlan
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 8dde7ed9628cae83725997632500a37401edde1eb6430d688ae5ea00bc988b11