pyopenms

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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.

Data & Documents 27,705 stars 2858 forks Updated today MIT

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# 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**:...

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Author
davila7
Repository
davila7/claude-code-templates
Created
11 months ago
Last Updated
today
Language
Python
License
MIT

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pyopenms

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.

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pyopenms

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.

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pyopenms

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.

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matchms

Spectral similarity and compound identification for metabolomics. Use for comparing mass spectra, computing similarity scores (cosine, modified cosine), and identifying unknown compounds from spectral libraries. Best for metabolite identification, spectral matching, library searching. For full LC-MS/MS proteomics pipelines use pyopenms.

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matchms

Spectral similarity and compound identification for metabolomics. Use for comparing mass spectra, computing similarity scores (cosine, modified cosine), and identifying unknown compounds from spectral libraries. Best for metabolite identification, spectral matching, library searching. For full LC-MS/MS proteomics pipelines use pyopenms.

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