MALDIcellassay: Automated MALDI Cell Assays Using Dose-Response Curve Fitting

Conduct automated cell-based assays using Matrix-Assisted Laser Desorption/Ionization (MALDI) methods for high-throughput screening of signals responsive to treatments. The package efficiently identifies high variance signals and fits dose-response curves to them. Quality metrics such as Z', V', log2FC, and CRS are provided for evaluating the potential of signals as biomarkers. The methodologies were introduced by Weigt et al. (2018) <doi:10.1038/s41598-018-29677-z> and refined by Unger et al. (2021) <doi:10.1038/s41596-021-00624-z>.

Version:	0.4.47
Depends:	R (≥ 4.2)
Imports:	methods, ggplot2, nplr, dplyr, tidyr, forcats, scales, MALDIquant, MALDIquantForeign, tibble, svMisc, purrr
Suggests:	rmarkdown, knitr
Published:	2024-08-29
DOI:	10.32614/CRAN.package.MALDIcellassay
Author:	Thomas Enzlein [aut, cre, cph]
Maintainer:	Thomas Enzlein <t.enzlein at hs-mannheim.de>
BugReports:	https://github.com/CeMOS-Mannheim/MALDIcellassay/issues
License:	MIT + file LICENSE
URL:	https://github.com/CeMOS-Mannheim/MALDIcellassay
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	MALDIcellassay results

Documentation:

Reference manual:	MALDIcellassay.pdf
Vignettes:	MALDI cell based assay Example (source, R code)

Downloads:

Package source:	MALDIcellassay_0.4.47.tar.gz
Windows binaries:	r-devel: MALDIcellassay_0.4.47.zip, r-release: MALDIcellassay_0.4.47.zip, r-oldrel: MALDIcellassay_0.4.47.zip
macOS binaries:	r-release (arm64): MALDIcellassay_0.4.47.tgz, r-oldrel (arm64): MALDIcellassay_0.4.47.tgz, r-release (x86_64): MALDIcellassay_0.4.47.tgz, r-oldrel (x86_64): MALDIcellassay_0.4.47.tgz

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