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! epiLION is a legacy project of Team SysMedOs.

The successor of epiLION is the LipidLynxX Project: https://github.com/SysMedOs/LipidLynxX

LipidLynxX provides the possibility to convert, cross-match, and link various lipid annotations to the tools supporting lipid ontology, pathway, and network analysis aiming systems-wide integration and functional annotation of lipidome dynamics in health and disease.

LipidLynx_Logo

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The LipidLynxX project is aimed to provide a unified identifier for major lipids, especially oxidized lipids in the epilipidome.

LipidLynxX on LIPID MAPS® Lipidomics Gateway

Thanks to LIPID MAPS, you can now use LipidLynxX on LIPID MAPS® Lipidomics Gateway

http://lipidmaps.org/lipidlynxx/

Please visit https://github.com/SysMedOs/LipidLynxX for more information.

About epiLION

epiLION_Logo

epiLipidome Identifier and Optimized Nomenclature

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The epiLION project is aimed to provide a unified identifier for major lipids, especially oxidized lipids in the epilipidome.

  • Main Features

    • Optimized for manual interpretation and computer processing
    • Unified modification controlled vocabularies
    • Unified position specific annotations
    • Special optimization for prostane containing lipids
    • Suitable for head group modified phospholipids
    • Hierarchical abbreviation system
    • Capable to parse fuzzy site unspecific annotations

epiLION_levels

  • epiLION abbreviation converter

    • Convert different abbreviations to uniformed epiLION abbreviations

epiLION_converter

  • epiLION structure and MS property generator

    • Abbreviation to SMILES/ MOL / SDF conversion using python

epiLION_generator

  • Currently supported modifications

    • DB: C=C bond
    • OH: hydroxy
    • Hp: hydroperoxy
    • NH2: amino
    • Me: methyl
    • Ke: keto/oxo
    • Ep: epoxy
    • SH: thio
    • My: methylene
    • Br: bromo
    • Cl: chloro
    • F: fluoro
    • CN: cyano
  • Example of epiLION abbreviations

    • Fatty acids

      • FA18:0
      • O-16:0
      • P-18:0
      • 20:4[4DB,2OH,1Ke]
      • 20:4[4DB{5Z,9E,11Z,14Z},1OH{8S}]
      • 20:4[4DB{5Z,9E,12E,15E},2OH{8S,11R},1Ke{14}]
    • Phospholipids

      • PC(O-16:0/18:1)
      • PC(P-16:0_18:1)
      • PC(16:0/20:4[4DB,2OH,1Ke])
      • PC(16:0/20:4[4DB{5,9,12,15},2OH{8,11},1Ke{14}])

Instructions

How to install epiLION from source code

  • Download the source code as zip file for your system

    • Download epiLION source Code as .zip. Please notice the date and version of LipidHunter source code.

    • Professional users can use git to clone the whole repository, please make sure that you switched to the correct branch.

    • Only the released version is recommended for real data processing. Other development branches may lead to unknown issues and miss interpretation of the data.

  • Rename the downloaded file to epiLION.zip

  • Unzip epiLION.zip file to any folder.

  • Install epiLION source code

    • epiLION is developed under python 3.6+.

    • The best way is to use virtual environment such as conda

    • Main dependencies are:

      • Data processing: pandas

      • SDF generation: rdkit

    • Test source code installation

  • Run epiLION converter

    • Run python convLION.py -i Test/TestInput/test_crosscheck.xlsx -o Test/TestOutput/test_crosscheck_output.xlsx

    • convLION read list of different abbreviations in the test_crosscheck.xlsx and generate the converted epiLION abbreviations in the output file.

    • convLION can read an write both .xlsx and .csv file.

    • sample input

      epiLION_converter_input

    • sample output

      epiLION_converter_output

  • Run epiLION generator

    • Run python epiLION.py -i Test/TestInput/test_names.txt -o Test/TestOutput/test_sdf.sdf

    • epiLION read list of epiLION abbreviations in the test_names.txt and generate the structure in a combined sdf file.

  • SDF output

  • Errors/bugs

    In case you experienced any problems with running LipidHunter

    please report an issue in the issue tracker or contact us.

License

  • LipidHunter is Dual-licensed

  • Please cite our publication in an appropriate form.

    • Ni, Zhixu, Laura Goracci, Gabriele Cruciani, and Maria Fedorova. "Computational solutions in redox lipidomics–Current strategies and future perspectives." Free Radical Biology and Medicine (2019). - DOI: 10.1016/j.freeradbiomed.2019.04.027

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We acknowledge all projects that supports the development of LipidHunter:

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