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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