ms-mint 0.1.6

Metabolomics Integrator (Mint)

ms-mint

A Python library for large-cohort metabolomics (MS1) processing

The Metabolomics Integrator (MINT) is a post-processing tool for liquid chromatography-mass spectrometry (LCMS) based metabolomics. Metabolomics is the study of all metabolites (small chemical compounds) in a biological sample e.g. from bacteria or a human blood sample. The metabolites can be used to define biomarkers used in medicine to find treatments for diseases or for the development of diagnostic tests or for the identification of pathogens such as methicillin resistant Staphylococcus aureus (MRSA). More information on how to install and run the program can be found in the Documentation.

The ms-mint library can be used for targeted metabolomics with large amounts of files (1000+). It uses a target list and the MS-filenames as input.

News

MINT has been split into the Python library and the app. This repository contains the Python library. For the app follow this link.

Contributions

All contributions, bug reports, code reviews, bug fixes, documentation improvements, enhancements, and ideas are welcome. Before you modify the code please reach out to us using the issues page.

Code standards

The project follows PEP8 standard and uses Black and Flake8 to ensure a consistent code format throughout the project.

Example usage

%pylab inline
from ms_mint.notebook import Mint
mint = Mint()

mint.ms_files = [
    './input/EC_B2.mzXML',
    './input/EC_B1.mzXML',
    './input/CA_B1.mzXML',
    './input/CA_B4.mzXML',
    './input/CA_B2.mzXML',
    './input/CA_B3.mzXML',
    './input/EC_B4.mzXML',
    './input/EC_B3.mzXML',
    './input/SA_B4.mzML',
    './input/SA_B2.mzML',
    './input/SA_B1.mzML',
    './input/SA_B3.mzML'
]

mint.load_targets('/home/swacker/workspace/ms-mint/tests/data/targets/targets_v0.csv')

mint.targets
>>>   peak_label    mz_mean  mz_width    rt  rt_min  rt_max  intensity_threshold target_filename
    0          1  151.06050         5  None    5.07    5.09                    0  targets_v0.csv
    1          2  216.05040         5  None    3.98    4.39                    0  targets_v0.csv
    2          3  115.00320         5  None    3.45    4.39                    0  targets_v0.csv
    3          4  273.00061         5  None    1.10    2.22                    0  targets_v0.csv

mint.run()

# Use mint.run(output_fn='results')

mint.results
>>>

mint.plot.hierarchical_clustering()

FAQ

What is a target list?

A target list is a pandas dataframe with specific columns.

• peak_label: str, Label of the peak (must be unique).
• mz_mean: float, m/z value of the target ion.
• mz_width: float, width of the peak in [ppm] of the mz_mean value.
• rt: float (optional), expected time of the peak maximum.
• rt_min: float, starting time for peak integration.
• rt_max: float, ending time for peak integration.
• intensity_threshold: float (>=0), minimum intensity value to include, serves as a noise filter.
• target_filename: str (optional), name of the target list file.

The target list can be stored as csv or Excel file.

What input files can be used?

ms_mint can be used with mzXML, mzML, mzMLb and experimental formats in .feather and .parquet format.