数据与复现统计与数据分析FreedomIntelligence/OpenClaw-Medical-Skills数据与复现
BI

bio-pathway-go-enrichment

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

bio-pathway-go-enrichment:Gene Ontology over-representation analysis ,使用 clusterProfiler enrichGO。 支持 all three ontologies (BP,MF,CC),multiple ID types,、 customizable statistical thresholds。 适合在identifying biological functions enriched in gene list ,面向 differential expression 或 other analyses时使用。

OpenClawNanoClaw分析处理复现实验bio-pathway-go-enrichment🧬 bioinformatics (gptomics bio-* suite)bioinformatics — pathway & network analysisgene

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-pathway-go-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

  • gene_ids <- bitr(sig_genes,fromType = 'SYMBOL',toType = 'ENTREZID',OrgDb = org.Hs.eg.db) gene_list <- gene_ids$ENTREZID。
  • converted <- bitr(genes,fromType = 'ENSEMBL',toType = 'ENTREZID',OrgDb = org.Hs.eg.db)。

原始文档

SKILL.md 摘录

Core Pattern

Goal: Identify enriched Gene Ontology terms in a gene list from differential expression or similar analyses.

Approach: Test for over-representation of GO terms using the hypergeometric test via clusterProfiler enrichGO.

"Run GO enrichment on my gene list" → Test whether biological process, molecular function, or cellular component terms are over-represented among significant genes.

Prepare Gene List from DE Results

Goal: Extract significant gene IDs from differential expression results and convert to the format required by enrichGO.

Approach: Filter DE results by adjusted p-value and fold change, then convert gene symbols to Entrez IDs using bitr.

library(dplyr)

de_results <- read.csv('de_results.csv')

sig_genes <- de_results %>%
    filter(padj < 0.05, abs(log2FoldChange) > 1) %>%
    pull(gene_id)

## ID Conversion with bitr

**Goal:** Convert between gene identifier types (Ensembl, Symbol, Entrez) for compatibility with enrichment tools.

**Approach:** Use clusterProfiler bitr to map between ID types using organism annotation databases.

```r

适用场景

  • 适合在identifying biological functions enriched in gene list ,面向 differential expression 或 other analyses时使用。

不适用场景

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

上游相关技能

  • kegg-pathways - KEGG pathway enrichment
  • gsea - Gene Set Enrichment Analysis for GO
  • enrichment-visualization - Visualize enrichment results
  • differential-expression - Generate input gene lists

相关技能

相关技能

返回目录
AR
数据与复现统计与数据分析

arxiv-database

arxiv-database:This skill provides Python tools ,用于 searching 、 retrieving preprints ,面向 arXiv.org ,通过 its public Atom A…

Claude Code分析处理
K-Dense-AI/claude-scientific-skills查看
BA
数据与复现统计与数据分析

bayesian-optimizer

bayesian-optimizer:Bayesian optimization ,用于 experimental design 、 hyperparameter tuning in biomedical research。

OpenClawNanoClaw分析处理
FreedomIntelligence/OpenClaw-Medical-Skills查看
BI
数据与复现统计与数据分析

bio-alignment-files-bam-statistics

bio-alignment-files-bam-statistics:Compute alignment statistics:flagstat,idxstats,coverage depth。

OpenClawNanoClaw分析处理
FreedomIntelligence/OpenClaw-Medical-Skills查看
BI
数据与复现统计与数据分析

bio-alignment-msa-statistics

bio-alignment-msa-statistics:Calculate alignment statistics ,涵盖 sequence identity,conservation scores,substitution matri…

OpenClawNanoClaw分析处理
FreedomIntelligence/OpenClaw-Medical-Skills查看