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If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

To cite lilikoi in publications use:

Fang X, Liu Y, Ren Z, Du Y, Huang Q, Garmire LX (2020). “Lilikoi V2.0: a deep-learning enabled, personalized pathway-based R package for diagnosis and prognosis predictions using metabolomics data.” bioRxiv. doi:10.1101/2020.07.09.195677, https://doi.org/10.1101/2020.07.09.195677.

AlAkwaa FM, Yunits B, Huang S, Alhajaji H, Garmire LX (2018). “Lilikoi: an R package for personalized pathway-based classification modeling using metabolomics data.” GigaScience, 7(12). https://doi.org/10.1093/gigascience/giy136.

Corresponding BibTeX entries:

  @Article{,
    title = {Lilikoi V2.0: a deep-learning enabled, personalized
      pathway-based R package for diagnosis and prognosis predictions
      using metabolomics data},
    author = {Xinying Fang and Yu Liu and Zhijie Ren and Yuheng Du and
      Qianhui Huang and Lana X. Garmire},
    journal = {bioRxiv},
    year = {2020},
    doi = {10.1101/2020.07.09.195677},
    url = {https://doi.org/10.1101/2020.07.09.195677},
  }
  @Article{,
    title = {Lilikoi: an R package for personalized pathway-based
      classification modeling using metabolomics data},
    author = {Fadhl M. AlAkwaa and Breck Yunits and Sijia Huang and
      Hassam Alhajaji and Lana X. Garmire},
    journal = {GigaScience},
    year = {2018},
    volume = {7},
    number = {12},
    url = {https://doi.org/10.1093/gigascience/giy136},
  }

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.