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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 |
| 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 |
| Reference manual: | lilikoi.pdf |
| Vignettes: |
Lilikoi V2.0 |
| 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 |
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These binaries (installable software) and packages are in development.
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