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
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.
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.
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This package is Dual-licensed
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For academic and non-commercial use: GPLv2 License:
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For commercial use: please contact the develop team by email.
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Please cite our publication in an appropriate form.
- Publication submitted
We acknowledge all projects that supports the development of LipidHunter:
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BMBF - Federal Ministry of Education and Research Germany:
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e:Med Systems Medicine Network:
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SysMedOS Project :