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LipidomeEstimation

This repository contains two python scripts for the estimation of lipidome in the unox/ox form.

Tested in Python 2.7, 3.6 and 3.7 with pandas and scipy on Windows an Linux

How to run the prediction

Navigate to the program folder

  • For the prediction of unox lipidome
$ python unoxlipidome_estimation.py
  • For the prediction of ox lipidome
$ python oxlipidome_estimation.py

The output will be displayed in the terminal.

Default values

The default FA list is in the data/FA_list.xlsx

The default lipid classes considered is defined as below:

usr_lipid_classes = {
    # list of lipid classes with 1 FA
    'x1': ['FA', 'CholesterolEster', 'LPA', 'LPC', 'LPE', 'LPG', 'LPI', 'LPS',
           'Monoacylglycerol', 'Ceramide', 'Sphingolipid'],
    # list of lipid classes with 2 FA
    'x2': ['PA', 'PC', 'PE', 'PG', 'PI', 'PS', 'Diacylglycerol'],
    'x3': ['Triacylglycerol'],  # list of lipid classes with 3 FA
    'x4': ['Cardiolipin'],  # list of lipid classes with 4 FA
}

The default lipid classes considered is defined as below:

usr_mod_dct = {
    'm_ocp': ['Aldehyde', 'CarboxylicAcid'],  # list of cleavage terminal
    'm_oap': ['OH', 'OOH', 'KETO', 'EPOXY'],  # list of Oxygen addition modifications
    'm_p': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J'],  # list of Prostane Rings
    'm_o': ['D-IsoK', 'E-IsoK', 'TXA', 'TXB'],  # list of Other types
}

The usr_lipid_classes and usr_mod_dct can be changed in the if __name__ == '__main__': section.

License

  • This package is Dual-licensed

    • For academic and non-commercial use: GPLv2 License:

    • For commercial use: please contact the develop team by email.

  • Please cite our publication in an appropriate form.

    • Publication submitted

Fundings

We acknowledge all projects that supports the development of LipidHunter:

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