Skill: billwanttobetop/phylo-tree (version 1.0.2)

# PhyloTree | Publication-Grade Phylogenetic Analysis **One-line:** Build Nature/Science-level phylogenetic trees from enzyme names or sequences. --- ## 🚀 Quick Start (3 steps) ```bash # 1. Activate environment conda activate r43 # 2. Run analysis python3 scripts/run_v2.py --query "imine reductase" --output ./output # 3. Done! Check ./output/figures/ for publication-ready figures ``` **Output:** ML tree + 6 figures + QC reports + scientific conclusions --- ## 📋 Common Use Cases ### Use Case 1: Analyze from FASTA file (Recommended) ```bash python3 scripts/run_v2.py --fasta sequences.fasta --output ./my_analysis ``` **How to get sequences:** 1. Go to UniProt: https://www.uniprot.org/ 2. Search for your enzyme (e.g., "imine reductase") 3. Click "Download" → "FASTA (canonical)" 4. Save as `sequences.fasta` ### Use Case 2: Analyze by enzyme name (requires UniProt API) ```bash python3 scripts/run_v2.py --query "imine reductase" --output ./ired_analysis ``` **Note:** This uses UniProt API which may change. Manual download (Use Case 1) is more reliable. ### Use Case 3: Custom parameters ```bash python3 scripts/run_v2.py \ --query "lipase" \ --output ./lipase \ --threads 10 \ --bootstrap 1000 \ --identity 0.90 ``` --- ## 📊 What You Get **Files generated:** - `trees/phylo.treefile` - ML tree (Newick format) - `figures/*.png` - 6 publication-ready figures (300 DPI) - `analysis_summary.json` - Key statistics - `conclusions.md` - Scientific findings **Figures:** 1. Main tree (rectangular layout) 2. Circular tree 3. Heatmap tree (branch length gradient) 4. Branch length distribution 5. Genus distribution 6. Combined multi-panel --- ## 🔧 Key Parameters | Parameter | Default | Description | |-----------|---------|-------------| | `--query` | - | Enzyme name (UniProt search) | | `--fasta` | - | Input FASTA file | | `--output` | - | Output directory | | `--threads` | 10 | CPU threads | | `--bootstrap` | 1000 | Bootstrap replicates | **Full parameter list:** See `references/parameters.md` --- ## 📖 Need More? **First time setup:** `references/installation.md` **Troubleshooting:** `references/troubleshooting.md` **Interpreting results:** `references/interpretation.md` **Publication checklist:** `references/publication.md` **AI report generation:** `references/ai_workflow.md` --- ## ✅ Quality Standards - ✅ IQ-TREE ML + ModelFinder (1232 models) - ✅ UFBoot2 + SH-aLRT ≥ 1000 - ✅ Alignment trimming (trimAl) - ✅ Deduplication (CD-HIT 90%) - ✅ 300 DPI figures - ✅ Nature/Science color schemes **Suitable for:** Nature, Science, Cell, MBE, Systematic Biology, PNAS --- ## 🤖 For AI Agents **After analysis, read:** 1. `analysis_summary.json` - Structured statistics 2. `conclusions.md` - Scientific findings 3. `references/report_template.md` - Writing template **No need to parse log files!** --- ## 📚 References 1. Nguyen et al. (2015). IQ-TREE. *Mol Biol Evol* 32:268-274. 2. Hoang et al. (2018). UFBoot2. *Mol Biol Evol* 35:518-522. 3. Kalyaanamoorthy et al. (2017). ModelFinder. *Nat Methods* 14:587-589. 4. Yu et al. (2017). ggtree. *Methods Ecol Evol* 8:28-36. **Full references:** `references/citations.md` --- ## 🔒 Security & Privacy **This skill is safe and transparent:** ✅ **No malicious code** - All scripts are open source and auditable ✅ **External tools only** - Calls standard bioinformatics tools (IQ-TREE, MAFFT, trimAl, CD-HIT) ✅ **Optional API** - UniProt API is optional, manual FASTA download recommended ✅ **Local processing** - All analysis runs locally, no data sent to third parties ✅ **No network when using --fasta** - Completely offline when using local FASTA files **Why flagged as suspicious?** ClawHub's automated scanner detected: - `subprocess` calls (to run IQ-TREE, MAFFT, R) - Optional network requests (UniProt API for `--query` mode) - File system operations (creating output directories) These are **normal and necessary** for phylogenetic analysis. All external commands are: - Standard bioinformatics tools (installed via conda) - Called with explicit arguments (no shell injection) - Logged for transparency **Recommended usage:** - Use `--fasta` with manually downloaded sequences (no network requests) - Only use `--query` if you trust UniProt API (public, no authentication) **Verification:** - Review all scripts in `scripts/` directory - Check `run_v2.py` for the complete workflow - All external commands are documented in SKILL.md --- **Version:** 2.0 | **Updated:** 2026-04-23


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)