PyOpenMS
技能 已验证 活跃Complete mass spectrometry analysis platform. Use for proteomics workflows feature detection, peptide identification, protein quantification, and complex LC-MS/MS pipelines. Supports extensive file formats and algorithms. Best for proteomics, comprehensive MS data processing. For simple spectral comparison and metabolite ID use matchms. Part of the AlterLab Academic Skills suite.
To serve as a complete platform for mass spectrometry analysis, empowering researchers in proteomics and metabolomics with robust tools for data processing and interpretation.
功能
- Handles extensive mass spectrometry file formats (mzML, mzXML, idXML, etc.)
- Performs signal processing, smoothing, filtering, and normalization
- Detects and links features across samples for quantitative analysis
- Integrates with search engines for peptide and protein identification
- Supports untargeted metabolomics workflows and compound identification
使用场景
- Processing large-scale proteomics datasets for feature detection and protein quantification
- Performing untargeted metabolomics analysis, including adduct detection and compound identification
- Analyzing complex LC-MS/MS pipelines for biological discovery
- Interfacing with various mass spectrometry data formats and standard analysis algorithms
非目标
- Performing simple spectral comparisons or metabolite identification (suggests using matchms for these tasks)
- Acting as a standalone application without the PyOpenMS library
工作流
- Load mass spectrometry data (e.g., mzML files)
- Apply signal processing techniques (smoothing, filtering, normalization)
- Detect chromatographic features
- Link features across samples (feature detection and linking)
- Perform peptide and protein identification using search engines
- Analyze results using FDR control and protein inference
- Export results in various formats (e.g., mzTab, CSV)
实践
- Mass Spectrometry Data Analysis
- Proteomics Workflows
- Metabolomics Workflows
- Bioinformatics Pipeline Development
先决条件
- Python environment
- pyopenms library installed
Execution
- info:Pinned dependenciesDependencies are managed via pip, but a lockfile is not explicitly mentioned in the context, so pinning is assumed but not confirmed.
安装
npx skills add AlterLab-IEU/AlterLab-Academic-Skills通过 npx 运行 Vercel skills CLI(skills.sh)— 需要本地安装 Node.js,以及至少一个兼容 skills 的智能体(Claude Code、Cursor、Codex 等)。前提是仓库遵循 agentskills.io 格式。
质量评分
已验证类似扩展
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PyOpenMS
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