Unknown

Dataset Information

0

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


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.

SUBMITTER: Al-Akwaa FM 

PROVIDER: S-EPMC6290884 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

altmetric image

Publications

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

Al-Akwaa Fadhl M FM   Yunits Breck B   Huang Sijia S   Alhajaji Hassam H   Garmire Lana X LX  

GigaScience 20181201 12


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 select  ...[more]

Similar Datasets

| S-EPMC7825009 | biostudies-literature
| S-EPMC5528809 | biostudies-other
| S-EPMC6770716 | biostudies-literature
| S-EPMC3224437 | biostudies-literature
| S-EPMC5447360 | biostudies-literature
| S-EPMC6303911 | biostudies-literature
| S-EPMC8615289 | biostudies-literature
| S-EPMC4033658 | biostudies-literature
| S-EPMC7423323 | biostudies-literature
| S-EPMC9851545 | biostudies-literature