Lilikoi: an R package for personalized pathway-based classification modeling using metabolomics data

Gigascience. 2018 Dec 1;7(12):giy136. doi: 10.1093/gigascience/giy136.

Abstract

Lilikoi (the Hawaiian word for passion fruit) is a new and comprehensive R package for personalized pathway-based classification modeling using metabolomics data. Four basic modules are presented as the backbone of the package: feature mapping module, which standardizes the metabolite names provided by users and maps them to pathways; dimension transformation module, which transforms the metabolomic profiles to personalized pathway-based profiles using pathway deregulation scores; feature selection module, which helps to select the significant pathway features related to the disease phenotypes; and classification and prediction module, which offers various machine learning classification algorithms. The package is freely available under the GPLv3 license through the github repository at: https://github.com/lanagarmire/lilikoi and CRAN: https://cran.r-project.org/web/packages/lilikoi/index.html.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Area Under Curve
  • Breast Neoplasms / metabolism
  • Breast Neoplasms / pathology
  • Female
  • Humans
  • Metabolomics / methods*
  • ROC Curve
  • Receptors, Estrogen / metabolism
  • User-Computer Interface*

Substances

  • Receptors, Estrogen