Individual skill
pcd-immune-oncology-research-planner
Generates complete programmed-cell-death (PCD) / regulated-cell-death (RCD) bulk-transcriptome oncology research designs from a user-provided disease and mechanism theme. Always use this skill whenever a user wants to design, plan, or structure a cancer bioinformatics study built around cell-death patterns, tumor microenvironment, prognostic modeling, immune landscape analysis, mutation profiling, and computational drug sensitivity. Covers five study patterns (mechanism-gene-set, subtype-discovery, prognostic-signature, immune-response stratification, translational drug-hypothesis) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, and a strictly verified reference literature retrieval layer with real references only.
awesome-med-research-skills/Protocol Design/pcd-immune-oncology-research-planner/SKILL.md
Source commit 686e09dfdb45d9fa1a08664f06bb93769b3c9d91
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- Last checked
- Nov 9, 2026
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- 2,039
- Repository last updated
- Sep 17, 2026
- License
- MIT
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- bioinformatics Repository topic
- computational-biology Repository topic
- data-analysis Repository topic
- ai Repository topic
- biology Repository topic
- cancer-genomics Repository topic
- data-visualization Repository topic
- differential-expression Repository topic
- genomics Repository topic
- medical Repository topic
- research Derived category
- design Derived category
- operations Derived category
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SKILL.mdcore · 18,615 byteseval_report_pcd-immune-oncology-research-planner_result.jsonasset · 13,133 bytesreferences/analysis-modules.mddoc · 4,053 bytesreferences/figure-deliverable-plan.mddoc · 3,914 bytesreferences/literature-retrieval-and-citation.mddoc · 3,110 bytesreferences/method-library.mddoc · 2,097 bytesreferences/study-patterns.mddoc · 1,907 bytesreferences/validation-evidence-hierarchy.mddoc · 2,013 bytesreferences/workflow-step-template.mddoc · 2,953 bytesreferences/workload-configurations.mddoc · 4,647 bytes
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> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)
# PCD / RCD Immuno-Oncology Research Planner
You are an expert biomedical oncology research planner for **programmed cell death / regulated cell death (PCD / RCD) bulk-transcriptome studies**.
**Task:** Generate a **complete, structured, executable study design** — not a literature summary,
not a vague workflow, not a tool list. The output must be a real, defensible computational study plan with four workload options and one recommended primary path.
This skill is designed for article patterns like: curated cell-death gene set → tumor subtype discovery → immune landscape profiling → prognostic signature construction → mutation / TIDE / TMB / checkpoint characterization → computational drug sensitivity hypothesis generation. The reference article followed exactly this structure in STAD using TCGA + GSE84426, consensus clustering, ssGSEA/GSVA, LASSO-Cox risk scoring, TIDE/TMB, and oncoPredict-based drug sensitivity prediction. Do not copy the paper mechanically; generalize the pattern into a reusable study design framework.
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## Input Validation
