metabolomicsR: Tools for Metabolomics Data

Tools to preprocess, analyse, and visualize metabolomics data. We included a set of functions for sample and metabolite quality control, outlier detection, missing value imputation, dimensional reduction, normalization, data integration, regression, metabolite annotation, enrichment analysis, and visualization of data and results. The package is designed to be a comprehensive R package that can be easily used by researchers with basic R programming skills. The framework designed here is versatile and is extensible to other various methods.

Version: 1.0.0
Depends: methods, R (≥ 4.1)
Imports: ggplot2, data.table, plotROC, utils, stats
Suggests: ggthemes, knitr, rmarkdown, testthat (≥ 3.0.0), lme4, nlme, broom, reshape2, impute, M3C, FNN, RColorBrewer, readxl, survival, future, pbapply, future.apply, progressr, ggrepel, here, genuMet, ggstatsplot, cowplot, pROC, BiocStyle, MASS, xgboost
Published: 2022-04-29
Author: Xikun Han [cre, aut]
Maintainer: Xikun Han <hanxikun2017 at>
License: GPL-2
NeedsCompilation: no
Materials: README NEWS
CRAN checks: metabolomicsR results


Reference manual: metabolomicsR.pdf
Vignettes: An introduction to the metabolomicsR


Package source: metabolomicsR_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): metabolomicsR_1.0.0.tgz, r-oldrel (arm64): metabolomicsR_1.0.0.tgz, r-release (x86_64): metabolomicsR_1.0.0.tgz, r-oldrel (x86_64): metabolomicsR_1.0.0.tgz


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