MetaClean: Detection of Low-Quality Peaks in Untargeted Metabolomics Data

Utilizes 11 peak quality metrics and 8 diverse machine learning algorithms to build a classifier for the automatic assessment of peak integration quality of peaks from untargeted metabolomics analyses. The 12 peak quality metrics were adapted from those defined in the following references: Zhang, W., & Zhao, P.X. (2014) <doi:10.1186/1471-2105-15-S11-S5> Toghi Eshghi, S., Auger, P., & Mathews, W.R. (2018) <doi:10.1186/s12014-018-9209-x>.

Version: 1.0.0
Depends: R (≥ 3.5.0), MLmetrics, xcms
Imports: reshape2, knitr, ggplot2, plotrix, tools, utils, klaR, fastAdaboost, rpart, randomForest, kernlab, BiocStyle, methods, graph, Rgraphviz, caret
Suggests: markdown
Published: 2020-09-11
Author: Kelsey Chetnik
Maintainer: Kelsey Chetnik <kchetnik73 at gmail.com>
License: GPL-3
NeedsCompilation: no
CRAN checks: MetaClean results

Documentation:

Reference manual: MetaClean.pdf
Vignettes: Create Peak Integration Quality Classifier for Assessment of Untargeted Metabolomics Features

Downloads:

Package source: MetaClean_1.0.0.tar.gz
Windows binaries: r-devel: MetaClean_1.0.0.zip, r-release: MetaClean_1.0.0.zip, r-oldrel: MetaClean_1.0.0.zip
macOS binaries: r-release (arm64): MetaClean_1.0.0.tgz, r-release (x86_64): MetaClean_1.0.0.tgz, r-oldrel: MetaClean_1.0.0.tgz
Old sources: MetaClean archive

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