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

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

Author information

1
Department of Computational Medicine and Bioinformatics, Building 520, 1600 Huron Parkway, Ann Arbor, MI 48109, USA.
2
University of Hawaii Cancer Center, Department of Epidemiology, 701 Ilalo Street, Honolulu, HI USA 96813.
3
Molecular Biology and Bioengineering Graduate Program, University of Hawaii at Monoa, Honolulu, HI, USA 96822.

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.

PMID:
30535020
PMCID:
PMC6290884
DOI:
10.1093/gigascience/giy136
[Indexed for MEDLINE]
Free PMC Article

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