数据与复现临床医学与医药FreedomIntelligence/OpenClaw-Medical-Skills数据与复现
TO

tooluniverse-gene-enrichment

维护者 FreedomIntelligence · 最近更新 2026年4月1日

Perform comprehensive gene enrichment and pathway analysis using gseapy (ORA and GSEA), PANTHER, STRING, Reactome, and 40+ ToolUniverse tools. Supports GO enrichment (BP, MF, CC), KEGG, Reactome, WikiPathways, MSigDB Hallmark, and 220+ Enrichr libraries. Handles multiple ID types (gene symbols, Ensembl, Entrez, UniProt), multiple organisms (human, mouse, rat, fly, worm, yeast), customizable backgrounds, and multiple….

OpenClawNanoClaw分析处理复现实验tooluniverse-gene-enrichment🏥 medical & clinicalmedical toolsperform

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/tooluniverse-gene-enrichment

维护者
FreedomIntelligence
许可
MIT
最近更新
2026年4月1日

技能摘要

来自 SKILL.md 的关键信息

2 min

核心说明

  • 执行 comprehensive gene enrichment analysis ,涵盖 Gene Ontology (GO),KEGG,Reactome,WikiPathways,、 MSigDB enrichment ,使用 both Over-Representation Analysis (ORA) 、 Gene Set Enrichment Analysis (GSEA). Integrates local computation ,通过 gseapy ,支持 ToolUniverse pathway databases ,用于 cross-validated,publication-ready results。
  • IMPORTANT:Always use English terms in tool calls (gene names,pathway names,organism names),even if user writes in another language. Only try original-language terms as fallback if English returns no results. Respond in user's language。
  • gene_list = ["TP53","BRCA1","EGFR"]。

原始文档

SKILL.md 摘录

When to Use This Skill

Apply when users:

  • Ask about gene enrichment analysis (GO, KEGG, Reactome, etc.)
  • Have a gene list from differential expression, clustering, or any experiment
  • Want to know which biological processes, molecular functions, or cellular components are enriched
  • Need KEGG or Reactome pathway enrichment analysis
  • Ask about GSEA (Gene Set Enrichment Analysis) with ranked gene lists
  • Want over-representation analysis (ORA) with Fisher's exact test
  • Need multiple testing correction (Benjamini-Hochberg, Bonferroni)
  • Ask about enrichGO, gseapy, clusterProfiler-style analyses

NOT for (use other skills instead):

  • Network pharmacology / drug repurposing → Use tooluniverse-network-pharmacology
  • Disease characterization → Use tooluniverse-multiomic-disease-characterization
  • Single gene function lookup → Use tooluniverse-disease-research
  • Spatial omics analysis → Use tooluniverse-spatial-omics-analysis
  • Protein-protein interaction analysis only → Use tooluniverse-protein-interactions

Input Parameters

ParameterRequiredDescriptionExample
gene_listYesList of gene symbols, Ensembl IDs, or Entrez IDs["TP53", "BRCA1", "EGFR"]
organismNoOrganism (default: human). Supported: human, mouse, rat, fly, worm, yeast, zebrafishhuman
analysis_typeNoORA (default) or GSEAORA
enrichment_databasesNoWhich databases to query. Default: all applicable["GO_BP", "GO_MF", "GO_CC", "KEGG", "Reactome"]
gene_id_typeNoInput ID type: symbol, ensembl, entrez, uniprot (auto-detected if omitted)symbol
p_value_cutoffNoSignificance threshold (default: 0.05)0.05
correction_methodNoMultiple testing: BH (Benjamini-Hochberg, default), bonferroni, fdrBH
background_genesNoCustom background gene set (default: genome-wide)["GENE1", "GENE2", ...]
ranked_gene_listNoFor GSEA: gene-to-score mapping (e.g., log2FC){"TP53": 2.5, "BRCA1": -1.3, ...}

适用场景

  • Ask about gene enrichment analysis (GO,KEGG,Reactome,etc.)。
  • Have gene list ,面向 differential expression,聚类,或 any experiment。
  • Want to know which biological processes,molecular functions,或 cellular components are enriched。
  • Need KEGG 或 Reactome pathway enrichment analysis。

不适用场景

  • Do not rely on this catalog entry alone ,用于 installation 或 maintenance details。

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