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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 |
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 |
Reference manual: | MALDIcellassay.pdf |
Vignettes: |
MALDI cell based assay Example (source, R code) |
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 |
Please use the canonical form https://CRAN.R-project.org/package=MALDIcellassay to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.