target-prioritizationlisted

Prioritize drug targets from a ranked gene list (e.g., scRNA-seq DE output) by orchestrating parallel API queries against UniProt, OpenTargets (with integrated DepMap CRISPR essentiality + gnomAD constraint), PubMed, the Human Protein Atlas (HPA), and ChEMBL tool compounds, then re-ranking by a composite score combining protein localization, druggability, disease genetics, tissue specificity (safety), focus-cell-type expression, CRISPR essentiality, LoF safety constraint, and research maturity. Use whenever the user wants to filter, triage, prioritize, or "do due diligence" on a list of candidate genes for drug discovery, especially after a DE / DEG analysis when they say things like "which of these should I follow up on", "filter for druggable targets", "make a target dossier", "rank these for tractability", "annotate these genes for druggability", or "build a target report". Trigger even when the user says just "filter these candidate genes" or hands over a CSV from a DE pipeline.
Agents365-ai/target-prioritization · ★ 3 · Data & Documents · score 62

Install: claude install-skill Agents365-ai/target-prioritization

# Target Prioritization A multi-source drug-target due-diligence pipeline for ranked gene lists. ## When this skill triggers The user has a list of candidate genes (typically from a DE / DEG / scRNA-seq analysis) and wants a per-gene dossier across multiple evidence dimensions plus a composite re-ranking. The DE statistical rank is just the entry point; the final priority is informed by protein biology, genetics, druggability, and research maturity. Common input shapes: - A CSV with a `gene` column (DE output like `expression_table_pass_either_1s.csv`) - A plain-text gene list (one symbol per line) - A list of symbols inline in the user's message ## Output Three files inside `<output_dir>/`: 1. **`targets_report.md`** — one section per gene, sorted by composite score, with a short LLM-written rationale and recommended next step 2. **`targets_summary.csv`** — flat table for sorting/filtering in Excel/pandas 3. **`raw_data/<source>.json`** — raw API responses (audit trail, reusable across future re-scorings) ## Pipeline ``` input gene list │ ▼ scripts/orchestrate.py │ ├─► fetch_uniprot.py → protein localization, surface, MHC, coding ├─► fetch_opentargets.py → tractability, approved drugs, associated │ diseases (subsumes GWAS Catalog via OT's │ integrated genetics evidence), DepMap CRISPR │ essentiality, gnomAD LOEUF / pLI constraint ├─► fetch