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tooluniverse-metabolomics-analysis
维护者 FreedomIntelligence · 最近更新 2026年4月1日
tooluniverse-metabolomics-analysis：分析 metabolomics data ，涵盖 metabolite identification，quantification，pathway analysis，、 metabolic flux。 Processes LC-MS，GC-MS，NMR data ，面向 targeted 、 untargeted experiments。 适合在analyzing metabolomics 数据集s，identifying differential metabolites，studying metabolic pathwa…时使用。
原始来源
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/tooluniverse-metabolomics-analysis
- 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
核心说明
- Comprehensive analysis of metabolomics data ，面向 metabolite identification through quantification，统计分析，pathway interpretation，、 integration ，支持 other omics layers。
- User has metabolomics data (LC-MS，GC-MS，NMR)。
- Questions about metabolite abundance 或 concentrations。
- Differential metabolite analysis requests。
- Metabolic pathway analysis。
原始文档
SKILL.md 摘录
Core Capabilities
| Capability | Description |
|---|---|
| Data Import | LC-MS, GC-MS, NMR, targeted/untargeted platforms |
| Metabolite Identification | Match to HMDB, KEGG, PubChem, spectral libraries |
| Quality Control | Peak quality, blank subtraction, internal standard normalization |
| Normalization | Probabilistic quotient, total ion current, internal standards |
| Statistical Analysis | Univariate and multivariate (PCA, PLS-DA, OPLS-DA) |
| Differential Analysis | Identify significant metabolite changes |
| Pathway Enrichment | KEGG, Reactome, BioCyc metabolic pathway analysis |
| Metabolite-Enzyme Integration | Correlate with expression data |
| Flux Analysis | Metabolic flux balance analysis (FBA) |
| Biomarker Discovery | Multi-metabolite signatures |
Phase 1: Data Import & Metabolite Identification
Objective: Load data and identify metabolites from features.
Supported data types:
- Peak tables: Pre-processed metabolite abundance
- Raw spectra: LC-MS (.mzML, .mzXML), GC-MS
- NMR spectra: 1D/2D NMR data
Peak table format (typical):
Data loading:
Metabolite identification:
Confidence scoring:
Phase 2: Quality Control & Filtering
Objective: Remove low-quality features and background noise.
Quality control metrics:
适用场景
- User has metabolomics data (LC-MS，GC-MS，NMR)。
- Questions about metabolite abundance 或 concentrations。
- Differential metabolite analysis requests。
- Metabolic pathway analysis。
不适用场景
- Do not rely on this catalog entry alone ，用于 installation 或 maintenance details。
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