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lilikoi: Metabolomics Personalized Pathway Analysis Tool

A comprehensive analysis tool for metabolomics data. It consists a variety of functional modules, including several new modules: a pre-processing module for normalization and imputation, an exploratory data analysis module for dimension reduction and source of variation analysis, a classification module with the new deep-learning method and other machine-learning methods, a prognosis module with cox-PH and neural-network based Cox-nnet methods, and pathway analysis module to visualize the pathway and interpret metabolite-pathway relationships. References: H. Paul Benton <http://www.metabolomics-forum.com/index.php?topic=281.0> Jeff Xia <https://github.com/cangfengzhe/Metabo/blob/master/MetaboAnalyst/website/name_match.R> Travers Ching, Xun Zhu, Lana X. Garmire (2018) <doi:10.1371/journal.pcbi.1006076>.

Version: 2.1.1
Depends: R (≥ 3.5.0)
Imports: car, caret, dplyr, gbm, ggplot2, glmnet, h2o, impute, infotheo, limma, M3C, Metrics, MLmetrics, parallel, princurve, pathview, plyr, preprocessCore, pROC, RCy3, reticulate, reshape, RWeka, scales, stats, stringr, survminer, survival
Suggests: knitr, rmarkdown
Published: 2022-10-05
DOI: 10.32614/CRAN.package.lilikoi
Author: Xinying Fang [aut], Yu Liu [aut], Zhijie Ren [aut], Fadhl Alakwaa [aut], Sijia Huang [aut], Lana Garmire [aut, cre]
Maintainer: Lana Garmire <lana.garmire.group at gmail.com>
License: GPL-2
NeedsCompilation: no
Citation: lilikoi citation info
Materials: README NEWS
In views: MissingData, Omics
CRAN checks: lilikoi results

Documentation:

Reference manual: lilikoi.pdf
Vignettes: Lilikoi V2.0

Downloads:

Package source: lilikoi_2.1.1.tar.gz
Windows binaries: r-devel: lilikoi_2.1.1.zip, r-release: lilikoi_2.1.1.zip, r-oldrel: lilikoi_2.1.1.zip
macOS binaries: r-release (arm64): lilikoi_2.1.1.tgz, r-oldrel (arm64): lilikoi_2.1.1.tgz, r-release (x86_64): lilikoi_2.1.1.tgz, r-oldrel (x86_64): lilikoi_2.1.1.tgz
Old sources: lilikoi archive

Linking:

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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.