pyOpenMS is an open-source Python library for
mass spectrometry<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<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 for
mass spectrometry<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
mzXML, mzML, TraML, mzTab,
FASTA <FASTA format>, pepxml, protxml, mzIdentML among others)- 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
background
installation first_steps introduction
datastructures_peak chemistry aasequences nasequences theoreticalspectrumgenerator spectrumalignment digestion datastructures_id datastructures_quant
parameter_handling algorithms smoothing centroiding normalization deisotoping feature_detection map_alignment feature_linking peptide_search chromatographic_analysis mzqc_export mass_decomposition GNPS_export
id_by_mz metabolomics_preprocessing
contribute
file_handling other_file_handling mzMLFileFormat hyperscore pandas_df_conversion massql memory_management pyopenms_in_r build_from_source wrap_classes interactive_plots ML_tutorial
apidoc
support faq glossary
genindex