القائمة
Shotgun metagenomics profiling — taxonomy, resistome, and functional pathways
يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.
اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
يتجاوز الأمر المباشر Prompt المخصّص للمراجعة. افحص المصدر قبل تشغيله.
npx skills add https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills --skill claw-metagenomicsيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
تفضّل نسخة محلية؟ نزّل الملفات المتاحة حاليًا لدى SkillsMP.
Convert raw Nanopore signal data (FAST5/POD5) to nucleotide sequences using Dorado basecaller. Covers model selection, GPU acceleration, modified base detection, and quality filtering. Use when processing raw Nanopore data before alignment. Guppy is deprecated; use Dorado for all new analyses.
Production-ready PDF processing with forms, tables, OCR, validation, and batch operations. Use when working with complex PDF workflows in production environments, processing large volumes of PDFs, or requiring robust error handling and validation.
Extract text and tables from PDF files, fill forms, merge documents. Use when working with PDF files or when the user mentions PDFs, forms, or document extraction.
عرض SKILL.md
| name | claw-metagenomics |
| version | 0.1.0 |
| description | Shotgun metagenomics profiling — taxonomy, resistome, and functional pathways |
| author | Manuel Corpas |
| license | MIT |
| tags | ["metagenomics","antimicrobial-resistance","taxonomy","functional-profiling","environmental","WHO-critical-ARGs"] |
| inputs | [{"name":"r1","type":"file","format":["fastq","fastq.gz","fq","fq.gz"],"description":"Forward reads (paired-end FASTQ R1)"},{"name":"r2","type":"file","format":["fastq","fastq.gz","fq","fq.gz"],"description":"Reverse reads (paired-end FASTQ R2)"},{"name":"input","type":"file","format":["fastq","fastq.gz","fq","fq.gz"],"description":"Single concatenated or interleaved FASTQ (alternative to R1+R2)"}] |
| outputs |
| [{"name":"taxonomy_report","type":"file","format":"tsv","description":"Bracken-adjusted species-level taxonomy abundance table"},{"name":"resistome_profile","type":"file","format":"tsv","description":"RGI/CARD antimicrobial resistance gene hits with WHO priority classification"},{"name":"functional_pathways","type":"file","format":"tsv","description":"HUMAnN3 pathway abundance table (MetaCyc/UniRef)"},{"name":"figures","type":"directory","format":["png","pdf"],"description":"Publication-quality figures (taxonomy bar chart, resistome heatmap, WHO-critical ARG summary)"},{"name":"reproducibility","type":"directory","description":"commands.sh, environment.yml, checksums.sha256"}] |
| metadata | {"openclaw":{"category":"bioinformatics","homepage":"https://github.com/ClawBio/ClawBio","min_python":"3.9","dependencies":["pandas","numpy","matplotlib","seaborn","scipy","biopython"],"system_dependencies":["kraken2","bracken","rgi","humann"]}} |
Comprehensive shotgun metagenomics analysis combining taxonomic classification, antimicrobial resistance gene detection, and functional pathway profiling from paired-end FASTQ files.
If you ask a general AI to "analyse a metagenome," it will:
This skill encodes the correct methodological decisions:
The skill works with any shotgun metagenome but has been validated on:
A key feature is the classification of detected resistance genes by WHO priority tier:
| Priority | Pathogen | Resistance |
|---|---|---|
| Critical | Acinetobacter baumannii | Carbapenem-resistant |
| Critical | Pseudomonas aeruginosa | Carbapenem-resistant |
| Critical | Enterobacteriaceae | Carbapenem-resistant, 3rd-gen cephalosporin-resistant |
| High | Enterococcus faecium | Vancomycin-resistant |
| High | Staphylococcus aureus | Methicillin-resistant, vancomycin-resistant |
| High | Helicobacter pylori | Clarithromycin-resistant |
| High | Campylobacter | Fluoroquinolone-resistant |
| High | Salmonella spp. | Fluoroquinolone-resistant |
| High | Neisseria gonorrhoeae | 3rd-gen cephalosporin-resistant, fluoroquinolone-resistant |
| Medium | Streptococcus pneumoniae | Penicillin-non-susceptible |
| Medium | Haemophilus influenzae | Ampicillin-resistant |
| Medium | Shigella spp. | Fluoroquinolone-resistant |
# Full pipeline (taxonomy + resistome + functional)
python metagenomics_profiler.py \
--r1 sample_R1.fastq.gz \
--r2 sample_R2.fastq.gz \
--output metagenomics_report
# Skip HUMAnN3 (faster — taxonomy + resistome only)
python metagenomics_profiler.py \
--r1 sample_R1.fastq.gz \
--r2 sample_R2.fastq.gz \
--output metagenomics_report \
--skip-functional
# Single concatenated FASTQ
python metagenomics_profiler.py \
--input combined.fastq.gz \
--output metagenomics_report
# Specify Kraken2 database path
python metagenomics_profiler.py \
--r1 sample_R1.fastq.gz \
--r2 sample_R2.fastq.gz \
--output metagenomics_report \
--kraken2-db /path/to/kraken2_db \
--read-length 150
python metagenomics_profiler.py --demo --output demo_report
The demo uses pre-computed results from the Peru sewage metagenomics study (6 samples, 3 sites) and generates all figures and reports instantly without requiring external tools.
Metagenomics Profiler — ClawBio
================================
Mode: demo (pre-computed Peru sewage data)
Samples: 6 (3 sites: Lima, Cusco, Iquitos)
Taxonomy (Kraken2 + Bracken):
Total classified: 94.2%
Top species: Escherichia coli (12.3%), Klebsiella pneumoniae (8.7%),
Pseudomonas aeruginosa (5.1%), Acinetobacter baumannii (3.9%)
Resistome (RGI/CARD):
Total ARG hits: 247 (Perfect: 89, Strict: 158)
Drug classes: 14
WHO-Critical ARGs detected: 23
- Carbapenem resistance: NDM-1, OXA-48, KPC-3
- 3rd-gen cephalosporin resistance: CTX-M-15, CTX-M-27
Functional Pathways (HUMAnN3):
Total pathways: 312
Top: PWY-7219 (adenosine ribonucleotides de novo biosynthesis)
Figures saved to: demo_report/figures/
taxonomy_barplot.png (300 dpi)
resistome_heatmap.png (300 dpi)
who_critical_args.png (300 dpi)
Reproducibility:
commands.sh | environment.yml | checksums.sha256
FASTQ R1 + R2
|
v
[Kraken2] --> kraken2_report.txt
|
v
[Bracken] --> bracken_species.tsv --> Figure 1: Taxonomy bar chart
|
v
[RGI MAIN] --> rgi_results.txt --> Figure 2: Resistome heatmap
| --> Figure 3: WHO-critical ARG summary
v
[HUMAnN3] --> pathabundance.tsv (optional, --skip-functional to omit)
|
v
[Report] --> report.md + figures/ + reproducibility/
| Tool | Database | Size | Notes |
|---|---|---|---|
| Kraken2 | Standard-8 or PlusPF | 8-70 GB | Set via --kraken2-db or $KRAKEN2_DB |
| Bracken | (built from Kraken2 DB) | included | Read-length specific (default: 150 bp) |
| RGI | CARD | ~500 MB | Auto-downloaded via rgi auto_load |
| HUMAnN3 | ChocoPhlAn + UniRef90 | ~15 GB | Set via --humann-db or $HUMANN_DB |
If you use this skill in a publication, please cite:
استنادا إلى تصنيف SOC المهني
