bioresearch-disease-case-studylisted

Run a reproducible, real-public-data disease case study that composes the literature → biomarker → causal workflows end-to-end and emits a blind benchmark evaluation (known-gene recovery, pathway sanity, reproducibility hash). Use when the user wants to prove the framework on a real disease (e.g. Parkinson's GSE7621) or asks for a "case study", "validation run", or "benchmark" of the biomedical workflows.
Alim430/bioresearch-agent · ★ 1 · AI & Automation · score 72

Install: claude install-skill Alim430/bioresearch-agent

# BioResearch Agent — Disease Case Study Skill ## Capability A **workflow-composition + validation** skill. It runs a real, public GEO dataset through the framework's analysis engine (differential expression → pathway enrichment → candidate ranking, with optional literature and causal-inference stages) and produces a **blind benchmark evaluation**: - **Known-gene recovery** — how many established disease genes surface in the top-ranked candidates (e.g. SNCA / LRRK2 / PARK7 / PINK1 / PRKN / GBA for Parkinson's). - **Pathway sanity** — whether disease-relevant pathways (dopamine / mitochondrial / oxidative / immune) are enriched. - **Reproducibility** — commit hash, environment, and data `sha256` recorded in an Evidence Package. Case Study 1 ships with the suite: **Parkinson's disease / GSE7621** (GPL570, 25 samples). See `bio-research-os/eval/case_study_pd.py` and the Biomedical Workflow Validation Suite README. ## Run ```bash python bio-research-os/eval/case_study_pd.py \ --matrix-path downloads/gse7621_matrix.txt.gz \ --annot-path downloads/gpl570.annot.gz \ --output-dir docs/case-study ``` (If paths are omitted the runner downloads the real GSE7621 matrix + GPL570 annotation itself.) ## Outputs (in `docs/case-study/`) - `GSE7621_deg.csv` — differential expression results - `GSE7621_top_candidates.csv` — ranked biomarker candidates - `GSE7621_pathway_enrichment.csv` — enriched KEGG / GO terms - `GSE7621_volcano.png` — volcano plot - `GSE7621_repo