[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6ECHB3BVZSRYJVR0TEWQP8V":3,"skill-same:01M6ECHB3BVZSRYJVR0TEWQP8V":71},{"skillNo":4,"name":5,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":7,"ownerLogin":8,"ownerAvatarUrl":9,"ownerAccountNo":10,"ownerDisplayName":11,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":22,"publishedAt":26,"linkOnly":27,"markdownContent":28,"markdownBody":28,"frontMatter":29,"refName":30,"commitSha":31,"skillDirectory":32,"forksCount":33,"repositoryHtmlUrl":34,"repositoryHomepageUrl":35,"ownerHtmlUrl":36,"ownerBlogUrl":6,"ownerDescription":37,"updatedAt":38,"install":39,"resources":52},"01M6ECHB3BVZSRYJVR0TEWQP8V","reactome-database",null,"ComeOnOliver\u002Fskillshub","ComeOnOliver","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F43215937?v=4","01M6E5JNFECJAAVFE0W7SMWWD2","Haoran Shu","01M6E5JNNDQS7AJZDYFQ8TPZCK",67,"MIT","https:\u002F\u002Fgithub.com\u002FComeOnOliver\u002Fskillshub\u002Fblob\u002Fmain\u002Fskills\u002FK-Dense-AI\u002Fclaude-scientific-skills\u002Freactome-database\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",[23,24,25],"database","reactome database","Reactome","2026-11-10 10:12:30",false,"# Reactome Database\n\n## Overview\n\nReactome is a free, open-source, curated pathway database with 2,825+ human pathways. Query biological pathways, perform overrepresentation and expression analysis, map genes to pathways, explore molecular interactions via REST API and Python client for systems biology research.\n\n## When to Use This Skill\n\nThis skill should be used when:\n- Performing pathway enrichment analysis on gene or protein lists\n- Analyzing gene expression data to identify relevant biological pathways\n- Querying specific pathway information, reactions, or molecular interactions\n- Mapping genes or proteins to biological pathways and processes\n- Exploring disease-related pathways and mechanisms\n- Visualizing analysis results in the Reactome Pathway Browser\n- Conducting comparative pathway analysis across species\n\n## Core Capabilities\n\nReactome provides two main API services and a Python client library:\n\n### 1. Content Service - Data Retrieval\n\nQuery and retrieve biological pathway data, molecular interactions, and entity information.\n\n**Common operations:**\n- Retrieve pathway information and hierarchies\n- Query specific entities (proteins, reactions, complexes)\n- Get participating molecules in pathways\n- Access database version and metadata\n- Explore pathway compartments and locations\n\n**API Base URL:** `https:\u002F\u002Freactome.org\u002FContentService`\n\n### 2. Analysis Service - Pathway Analysis\n\nPerform computational analysis on gene lists and expression data.\n\n**Analysis types:**\n- **Overrepresentation Analysis**: Identify statistically significant pathways from gene\u002Fprotein lists\n- **Expression Data Analysis**: Analyze gene expression datasets to find relevant pathways\n- **Species Comparison**: Compare pathway data across different organisms\n\n**API Base URL:** `https:\u002F\u002Freactome.org\u002FAnalysisService`\n\n### 3. reactome2py Python Package\n\nPython client library that wraps Reactome API calls for easier programmatic access.\n\n**Installation:**\n```bash\nuv pip install reactome2py\n```\n\n**Note:** The reactome2py package (version 3.0.0, released January 2021) is functional but not actively maintained. For the most up-to-date functionality, consider using direct REST API calls.\n\n## Querying Pathway Data\n\n### Using Content Service REST API\n\nThe Content Service uses REST protocol and returns data in JSON or plain text formats.\n\n**Get database version:**\n```python\nimport requests\n\nresponse = requests.get(\"https:\u002F\u002Freactome.org\u002FContentService\u002Fdata\u002Fdatabase\u002Fversion\")\nversion = response.text\nprint(f\"Reactome version: {version}\")\n```\n\n**Query a specific entity:**\n```python\nimport requests\n\nentity_id = \"R-HSA-69278\"  # Example pathway ID\nresponse = requests.get(f\"https:\u002F\u002Freactome.org\u002FContentService\u002Fdata\u002Fquery\u002F{entity_id}\")\ndata = response.json()\n```\n\n**Get participating molecules in a pathway:**\n```python\nimport requests\n\nevent_id = \"R-HSA-69278\"\nresponse = requests.get(\n    f\"https:\u002F\u002Freactome.org\u002FContentService\u002Fdata\u002Fevent\u002F{event_id}\u002FparticipatingPhysicalEntities\"\n)\nmolecules = response.json()\n```\n\n### Using reactome2py Package\n\n```python\nimport reactome2py\nfrom reactome2py import content\n\n# Query pathway information\npathway_info = content.query_by_id(\"R-HSA-69278\")\n\n# Get database version\nversion = content.get_database_version()\n```\n\n**For detailed API endpoints and parameters**, refer to `references\u002Fapi_reference.md` in this skill.\n\n## Performing Pathway Analysis\n\n### Overrepresentation Analysis\n\nSubmit a list of gene\u002Fprotein identifiers to find enriched pathways.\n\n**Using REST API:**\n```python\nimport requests\n\n# Prepare identifier list\nidentifiers = [\"TP53\", \"BRCA1\", \"EGFR\", \"MYC\"]\ndata = \"\\n\".join(identifiers)\n\n# Submit analysis\nresponse = requests.post(\n    \"https:\u002F\u002Freactome.org\u002FAnalysisService\u002Fidentifiers\u002F\",\n    headers={\"Content-Type\": \"text\u002Fplain\"},\n    data=data\n)\n\nresult = response.json()\ntoken = result[\"summary\"][\"token\"]  # Save token to retrieve results later\n\n# Access pathways\nfor pathway in result[\"pathways\"]:\n    print(f\"{pathway['stId']}: {pathway['name']} (p-value: {pathway['entities']['pValue']})\")\n```\n\n**Retrieve analysis by token:**\n```python\n# Token is valid for 7 days\nresponse = requests.get(f\"https:\u002F\u002Freactome.org\u002FAnalysisService\u002Ftoken\u002F{token}\")\nresults = response.json()\n```\n\n### Expression Data Analysis\n\nAnalyze gene expression datasets with quantitative values.\n\n**Input format (TSV with header starting with #):**\n```\n#Gene\tSample1\tSample2\tSample3\nTP53\t2.5\t3.1\t2.8\nBRCA1\t1.2\t1.5\t1.3\nEGFR\t4.5\t4.2\t4.8\n```\n\n**Submit expression data:**\n```python\nimport requests\n\n# Read TSV file\nwith open(\"expression_data.tsv\", \"r\") as f:\n    data = f.read()\n\nresponse = requests.post(\n    \"https:\u002F\u002Freactome.org\u002FAnalysisService\u002Fidentifiers\u002F\",\n    headers={\"Content-Type\": \"text\u002Fplain\"},\n    data=data\n)\n\nresult = response.json()\n```\n\n### Species Projection\n\nMap identifiers to human pathways exclusively using the `\u002Fprojection\u002F` endpoint:\n\n```python\nresponse = requests.post(\n    \"https:\u002F\u002Freactome.org\u002FAnalysisService\u002Fidentifiers\u002Fprojection\u002F\",\n    headers={\"Content-Type\": \"text\u002Fplain\"},\n    data=data\n)\n```\n\n## Visualizing Results\n\nAnalysis results can be visualized in the Reactome Pathway Browser by constructing URLs with the analysis token:\n\n```python\ntoken = result[\"summary\"][\"token\"]\npathway_id = \"R-HSA-69278\"\nurl = f\"https:\u002F\u002Freactome.org\u002FPathwayBrowser\u002F#{pathway_id}&DTAB=AN&ANALYSIS={token}\"\nprint(f\"View results: {url}\")\n```\n\n## Working with Analysis Tokens\n\n- Analysis tokens are valid for **7 days**\n- Tokens allow retrieval of previously computed results without re-submission\n- Store tokens to access results across sessions\n- Use `GET \u002Ftoken\u002F{TOKEN}` endpoint to retrieve results\n\n## Data Formats and Identifiers\n\n### Supported Identifier Types\n\nReactome accepts various identifier formats:\n- UniProt accessions (e.g., P04637)\n- Gene symbols (e.g., TP53)\n- Ensembl IDs (e.g., ENSG00000141510)\n- EntrezGene IDs (e.g., 7157)\n- ChEBI IDs for small molecules\n\nThe system automatically detects identifier types.\n\n### Input Format Requirements\n\n**For overrepresentation analysis:**\n- Plain text list of identifiers (one per line)\n- OR single column in TSV format\n\n**For expression analysis:**\n- TSV format with mandatory header row starting with \"#\"\n- Column 1: identifiers\n- Columns 2+: numeric expression values\n- Use period (.) as decimal separator\n\n### Output Format\n\nAll API responses return JSON containing:\n- `pathways`: Array of enriched pathways with statistical metrics\n- `summary`: Analysis metadata and token\n- `entities`: Matched and unmapped identifiers\n- Statistical values: pValue, FDR (false discovery rate)\n\n## Helper Scripts\n\nThis skill includes `scripts\u002Freactome_query.py`, a helper script for common Reactome operations:\n\n```bash\n# Query pathway information\npython scripts\u002Freactome_query.py query R-HSA-69278\n\n# Perform overrepresentation analysis\npython scripts\u002Freactome_query.py analyze gene_list.txt\n\n# Get database version\npython scripts\u002Freactome_query.py version\n```\n\n## Additional Resources\n\n- **API Documentation**: https:\u002F\u002Freactome.org\u002Fdev\n- **User Guide**: https:\u002F\u002Freactome.org\u002Fuserguide\n- **Documentation Portal**: https:\u002F\u002Freactome.org\u002Fdocumentation\n- **Data Downloads**: https:\u002F\u002Freactome.org\u002Fdownload-data\n- **reactome2py Docs**: https:\u002F\u002Freactome.github.io\u002Freactome2py\u002F\n\nFor comprehensive API endpoint documentation, see `references\u002Fapi_reference.md` in this skill.\n\n## Current Database Statistics (Version 94, September 2025)\n\n- 2,825 human pathways\n- 16,002 reactions\n- 11,630 proteins\n- 2,176 small molecules\n- 1,070 drugs\n- 41,373 literature references\n",{},"main","def8531e65114c0fca8fb8551c1871ee0eed705c","skills\u002FK-Dense-AI\u002Fclaude-scientific-skills\u002Freactome-database",24,"https:\u002F\u002Fgithub.com\u002FComeOnOliver\u002Fskillshub","https:\u002F\u002Fskillshub.wtf","https:\u002F\u002Fgithub.com\u002FComeOnOliver","AI & Blockchain Engineer\r\n","2026-06-24 22:07:19",{"source":7,"skillName":5,"commands":40,"prompt":50,"zipAvailable":51},[41,44,47],{"tool":42,"command":43},"npx","npx skills add ComeOnOliver\u002Fskillshub --skill reactome-database",{"tool":45,"command":46},"bunx","bunx skills add ComeOnOliver\u002Fskillshub --skill reactome-database",{"tool":48,"command":49},"pnpm","pnpm dlx skills add ComeOnOliver\u002Fskillshub --skill reactome-database","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FComeOnOliver\u002Fskillshub\u002Fblob\u002Fmain\u002Fskills\u002FK-Dense-AI\u002Fclaude-scientific-skills\u002Freactome-database\u002FSKILL.md",true,[53,59,65],{"path":54,"resourceType":55,"resourceTypeDesc":56,"sizeBytes":57,"sourceHtmlUrl":58},"customize.toml","OTHER","其他",1722,"https:\u002F\u002Fgithub.com\u002FAkallabet\u002Fthings4\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fbmad-cis-problem-solving\u002Fcustomize.toml",{"path":60,"resourceType":61,"resourceTypeDesc":62,"sizeBytes":63,"sourceHtmlUrl":64},"solving-methods.csv","ASSET","资产文件",7311,"https:\u002F\u002Fgithub.com\u002FAkallabet\u002Fthings4\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fbmad-cis-problem-solving\u002Fsolving-methods.csv",{"path":66,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":69,"sourceHtmlUrl":70},"template.md","REFERENCE","参考文档",2001,"https:\u002F\u002Fgithub.com\u002FAkallabet\u002Fthings4\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fbmad-cis-problem-solving\u002Ftemplate.md",[72,84,94,103,109,116],{"skillNo":73,"name":74,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":7,"ownerLogin":8,"ownerAvatarUrl":9,"ownerAccountNo":10,"ownerDisplayName":11,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":75,"categories":76,"keywords":80,"publishedAt":26},"01M6FKJN13GMG4KY57J3QD8GY5","model-hierarchy-skill","https:\u002F\u002Fgithub.com\u002FComeOnOliver\u002Fskillshub\u002Fblob\u002Fmain\u002Fskills\u002Fzscole\u002Fmodel-hierarchy-skill\u002Fmodel-hierarchy-skill\u002FSKILL.md",[77],{"categoryNo":78,"categoryName":79,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",[81,82,83],"model","model hierarchy","model hierarchy skill",{"skillNo":85,"name":86,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":7,"ownerLogin":8,"ownerAvatarUrl":9,"ownerAccountNo":10,"ownerDisplayName":11,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":87,"categories":88,"keywords":90,"publishedAt":26},"01M6FKJJJ6GCAMR4PPPRD12M5X","zoom-mcp","https:\u002F\u002Fgithub.com\u002FComeOnOliver\u002Fskillshub\u002Fblob\u002Fmain\u002Fskills\u002Fzoom\u002Fskills\u002Fzoom-mcp\u002FSKILL.md",[89],{"categoryNo":78,"categoryName":79,"taxonomyType":20,"taxonomyTypeDesc":21},[91,92,93],"MCP","zoom","zoom mcp",{"skillNo":95,"name":96,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":7,"ownerLogin":8,"ownerAvatarUrl":9,"ownerAccountNo":10,"ownerDisplayName":11,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":97,"categories":98,"keywords":99,"publishedAt":26},"01M6FKJE3KYT3KPEZMEEHYKA6K","zoom-apps-sdk","https:\u002F\u002Fgithub.com\u002FComeOnOliver\u002Fskillshub\u002Fblob\u002Fmain\u002Fskills\u002Fzoom\u002Fskills\u002Fzoom-apps-sdk\u002FSKILL.md",[],[100,101,102,92],"sdk","zoom apps sdk","apps",{"skillNo":104,"name":105,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":7,"ownerLogin":8,"ownerAvatarUrl":9,"ownerAccountNo":10,"ownerDisplayName":11,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":106,"categories":107,"keywords":108,"publishedAt":26},"01M6FKJ9EDH9Q5VWDF8HAJRSP0","windows","https:\u002F\u002Fgithub.com\u002FComeOnOliver\u002Fskillshub\u002Fblob\u002Fmain\u002Fskills\u002Fzoom\u002Fskills\u002Fwindows\u002FSKILL.md",[],[105],{"skillNo":110,"name":111,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":7,"ownerLogin":8,"ownerAvatarUrl":9,"ownerAccountNo":10,"ownerDisplayName":11,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":112,"categories":113,"keywords":115,"publishedAt":26},"01M6FKJ666BEEFC3AE9GJ72Q93","whiteboard","https:\u002F\u002Fgithub.com\u002FComeOnOliver\u002Fskillshub\u002Fblob\u002Fmain\u002Fskills\u002Fzoom\u002Fskills\u002Fwhiteboard\u002FSKILL.md",[114],{"categoryNo":78,"categoryName":79,"taxonomyType":20,"taxonomyTypeDesc":21},[111],{"skillNo":117,"name":118,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":7,"ownerLogin":8,"ownerAvatarUrl":9,"ownerAccountNo":10,"ownerDisplayName":11,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":119,"categories":120,"keywords":121,"publishedAt":26},"01M6FKJ21WFCDGTJQ2Q91T9DVW","websockets","https:\u002F\u002Fgithub.com\u002FComeOnOliver\u002Fskillshub\u002Fblob\u002Fmain\u002Fskills\u002Fzoom\u002Fskills\u002Fwebsockets\u002FSKILL.md",[],[118]]