本文へ移動
cccskills
無料GitHub で公開

ngs-shotgun-metagenomics

Kick off public shotgun metagenomics QC, host-depletion, taxonomic profiling, and functional profiling workflows using nf-core/taxprofiler, Kraken2, Bracken, MetaPhlAn, and HUMAnN.

インストール方法を見る

含まれるファイル(2)

  • SKILL.md4.8 KB
  • agents/openai.yaml288 B

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

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

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:

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:

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:

nextflow run nf-core/taxprofiler \
  -profile test,docker \
  --outdir results/taxprofiler_test

Direct Kraken2 skeleton:

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.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Make data visualizations accessible and inclusive. Use when the user needs chart or diagram accessibility guidance, text alternatives for complex visuals, color and contrast review, keyboard support, reduced-motion behavior for animation or parallax, or an accessibility QA workflow for exported figures, UML-like diagrams, and dashboards.

日本語の概要は準備中です。原文の説明を表示しています。

openai/plugins7,4262026年10月8日 更新

Apply consistent photo adjustments across a set of images so they look like they were edited together. Use this skill whenever the user says "make my photos look cohesive", "give all these the same style", "apply a warm and golden feel to all of these", "make this cinematic", "match the look across my photos", "edit all my travel photos the same way", "batch edit these", "make these consistent", "fix my phone photos", or uploads a folder of photos and wants a unified, polished result. Also triggers for requests like "apply a preset to all of these", "make these look professional", or "they were shot in mixed lighting — can you fix them all". Outputs direct final image URLs plus an in-chat preview grid and optional Firefly Board link. Access: 🔐 Signed-In required | Gen AI: ❌

日本語の概要は準備中です。原文の説明を表示しています。

openai/plugins7,4262026年10月8日 更新

Use when a user wants to see their logo, design, or sketch on a product or scene mockup — mugs, t-shirts, business cards, hats, phone screens, posters, billboards, or similar. Triggers on "create mockups", "show my logo on products", or any logo upload with a request to visualize it on items. Access: 🔐 Signed-In required | Gen AI: ✅ Adobe Firefly via `image_generate` used for design creation, sketch polishing, and mockup scene generation

日本語の概要は準備中です。原文の説明を表示しています。

openai/plugins7,4262026年10月8日 更新

Resize, crop, or export any image or video into platform-ready social media assets using Adobe Creative Cloud tools. Use this skill when a user wants to prepare a photo, image, or video for one or more social platforms — Instagram, TikTok, LinkedIn, Facebook, YouTube, Snapchat, Pinterest, Threads, or X/Twitter. Triggers on: "prepare my image for Instagram", "resize for TikTok", "get this ready to post", "make versions for all platforms", "social media sizes", "crop for stories", "export for LinkedIn", "resize my video for social", "make social media assets", or any request to adapt a photo or video for specific platforms. Handles subject-aware cropping, AI canvas expansion, test previews before full runs, and same-ratio video resizing.

日本語の概要は準備中です。原文の説明を表示しています。

openai/plugins7,4262026年10月8日 更新

Create any visual design using Adobe Express templates — flyers, posters, social media posts (Instagram, Facebook, LinkedIn), business cards, invitations, greeting cards, resumes, cover letters, brochures, newsletters, certificates, presentations, YouTube thumbnails, email headers, logos, menus, and labels. Use this skill whenever the user wants to make, design, or build any visual — even if they just say "make me a flyer", "design a poster", "I need something for Instagram", "create an event invite", or "make a business card". Also handles browsing templates, editing text, replacing images, changing backgrounds, animating, and exporting designs. Access: 🔐 Signed-In required | Gen AI: ❌ by default — image replacement only where the surface permits generative AI (e.g. Codex); none on Claude

日本語の概要は準備中です。原文の説明を表示しています。

openai/plugins7,4262026年10月8日 更新

Create a punchy sizzle reel from a video using Adobe Quick Cut. Use this skill whenever a user wants to cut, trim, or shorten a video into highlights — including phrases like "make a sizzle reel", "make a highlight reel", "quick cut this", "cut the best parts", "shorten this video", "make a highlight clip", "summarize this video visually", or any request to produce a shorter edited version of a video. Use this skill for Quick Cut requests before suggesting manual editing in Premiere. Requires the user to upload a video file.

日本語の概要は準備中です。原文の説明を表示しています。

openai/plugins7,4262026年10月8日 更新

openai のスキルをすべて見る

このスキルの問題を報告する