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pyopenmslisted

Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML, mzTab, FASTA, pepXML, protXML, mzIdentML), signal processing, feature detection, peptide identification, and quantitative analysis. Apply when working with mass spectrometry data, analyzing proteomics experiments, or processing metabolomics datasets.
aiskillstore/marketplace · ★ 334 · Data & Documents · score 80
Install: claude install-skill aiskillstore/marketplace
# PyOpenMS ## Overview PyOpenMS provides Python bindings to the OpenMS library for computational mass spectrometry, enabling analysis of proteomics and metabolomics data. Use for handling mass spectrometry file formats, processing spectral data, detecting features, identifying peptides/proteins, and performing quantitative analysis. ## Installation Install using uv: ```bash uv uv pip install pyopenms ``` Verify installation: ```python import pyopenms print(pyopenms.__version__) ``` ## Core Capabilities PyOpenMS organizes functionality into these domains: ### 1. File I/O and Data Formats Handle mass spectrometry file formats and convert between representations. **Supported formats**: mzML, mzXML, TraML, mzTab, FASTA, pepXML, protXML, mzIdentML, featureXML, consensusXML, idXML Basic file reading: ```python import pyopenms as ms # Read mzML file exp = ms.MSExperiment() ms.MzMLFile().load("data.mzML", exp) # Access spectra for spectrum in exp: mz, intensity = spectrum.get_peaks() print(f"Spectrum: {len(mz)} peaks") ``` **For detailed file handling**: See `references/file_io.md` ### 2. Signal Processing Process raw spectral data with smoothing, filtering, centroiding, and normalization. Basic spectrum processing: ```python # Smooth spectrum with Gaussian filter gaussian = ms.GaussFilter() params = gaussian.getParameters() params.setValue("gaussian_width", 0.1) gaussian.setParameters(params) gaussian.filterExperiment(exp) ``` **For algorithm details**: