pyopenms

Process mass spectrometry data for proteomics and metabolomics workflows.

Updated Mar 10, 2026

Search Tags:#data analysis #metabolomics #mass spectrometry #proteomics #pyopenms #lc-ms/ms

Ready to run

npx skills add https://github.com/felixboehm/biochem-allergy --skill pyopenms-felixboehm

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: pyopenms
Source: https://github.com/felixboehm/biochem-allergy/tree/main/.claude/skills/pyopenms
Command: npx skills add https://github.com/felixboehm/biochem-allergy --skill pyopenms-felixboehm

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill simplifies complex mass spectrometry data analysis, enabling researchers to process proteomics and metabolomics data efficiently without deep programming expertise.

Core Features & Use Cases

Data Processing: Handle various MS file formats, perform signal processing, and detect features.
Identification & Quantification: Facilitate peptide/protein identification and quantitative analysis.
Use Case: Analyze raw LC-MS/MS data to identify and quantify proteins in a biological sample, generating a comprehensive list of identified proteins with their associated scores and confidence levels.

Quick Start

Use the pyopenms skill to load 'sample.mzML' and print the number of spectra.

Frequently Asked Questions about pyopenms

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I analyze raw LC-MS/MS data to identify and quantify proteins?▼

You can analyze raw LC-MS/MS data to identify and quantify proteins by loading mzML files to perform signal processing, feature detection, and peptide identification, generating a list of identified proteins with associated confidence scores.

What mass spectrometry file formats are supported for proteomics and metabolomics workflows?▼

Mass spectrometry workflows support extensive file formats for proteomics and metabolomics data processing, allowing you to load standard files like mzML to handle spectra input and output seamlessly.

Do I need deep programming expertise to process mass spectrometry data?▼

You do not need deep programming expertise to process mass spectrometry data. This platform simplifies complex MS data analysis, enabling researchers to execute signal processing and feature detection efficiently.

Can I perform both peptide identification and quantification in the same mass spectrometry workflow?▼

Yes, you can perform both peptide identification and quantification within the same mass spectrometry workflow. The platform facilitates comprehensive protein identification and quantitative analysis from your biological samples.

What is the best way to detect features in LC-MS/MS data without writing extensive code?▼

The best way to detect features in LC-MS/MS data without extensive code is using a platform that simplifies signal processing and feature detection, allowing you to process raw biological samples efficiently.

How do I get started with loading mzML files for mass spectrometry data analysis?▼

To get started with mass spectrometry data analysis, you can load a sample mzML file to read the spectra and print the number of spectra, serving as a quick test for your file input and output setup.