Summary
pyOpenMS is an open-source Python library for mass spectrometry, specifically for the analysis of proteomics and metabolomics data in Python. pyOpenMS implements a set of Python bindings to the OpenMS library for computational mass spectrometry and is available for Windows, Linux and OSX.
PyOpenMS provides functionality that is commonly used in computational mass spectrometry. The pyOpenMS package contains Python bindings for a large part of the OpenMS library (http://www.openms.de) for mass spectrometry based proteomics. It thus provides facile access to a feature-rich, open-source algorithm library for mass-spectrometry based proteomics analysis.
pyOpenMS facilitates the execution of common tasks in proteomics (and other mass spectrometric fields) such as
file handling (mzXML, mzML, TraML, mzTab, fasta, pepxml, protxml, mzIdentML among others)
chemistry (mass calculation, peptide fragmentation, isotopic abundances)
signal processing (smoothing, filtering, de-isotoping, retention time correction and peak-picking)
identification analysis (including peptide search, PTM analysis, Cross-linked analytes, FDR control, RNA oligonucleotide search and small molecule search tools)
quantitative analysis (including label-free, metabolomics, SILAC, iTRAQ and SWATH/DIA analysis tools)
chromatogram analysis (chromatographic peak picking, smoothing, elution profiles and peak scoring for SRM/MRM/PRM/SWATH/DIA data)
interaction with common tools in proteomics and metabolomics
search engines such as Comet, Crux, Mascot, MSGFPlus, MSFragger, Myrimatch, OMSSA, Sequest, SpectraST, XTandem
post-processing tools such as percolator, MSStats, Fido
metabolomics tools such as SIRIUS, CSI:FingerId
- Identification by Accurate Mass
- Imports and mzML file path
- Download Example Data
- Centroiding
- Feature Detection
- Feature Map Retention Time Alignment
- Visualization of RTs before and after alignment
- Feature Linking
- ConsensusMap to pandas DataFrame
- Accurate Mass Search
- Data Filtering and Imputation
- Annotate features with identified compounds
- Visualize consensus features with identifications
- Untargeted Metabolomics Pre-Processing