TidyMS is a python library for processing Mass Spectrometry data. It aims to provide easy to use tools to read, process and visualize MS data generated in metabolomic studies.
TidyMS provides functionality to:
- Read raw MS data in the mzML format
- Spectrum and chromatogram creation.
- Powerful and flexible peak picking functions optimized for chromatographic and spectral data.
- Feature detection and feature correspondence in LC-MS data.
- Reading processed data in a variety of formats (XCMS, MZMine2, ...)
- Data matrix curation using widely accepted guidelines from the metabolomics community.
- Interactive visualizations of raw and processed data using Bokeh, or publication quality plots using seaborn.
The latest release can be installed from PyPI:
pip install tidyms
Jupyter notebooks with examples are available here.
TidyMS uses unit tests for most of its functionality. The tests can be executed with
python setup.py test
The official documentation is available at readthedocs.
If you find TidyMS useful, we would appreciate citations:
Riquelme, G.; Zabalegui, N.; Marchi, P.; Jones, C.M.; Monge, M.E. A Python-Based Pipeline for Preprocessing LC–MS Data for Untargeted Metabolomics Workflows. Metabolites 2020, 10, 416, doi:10.3390/metabo10100416.