Analysis of single-cell RNA sequencing data can be simple and clear with the right utility functions. This package collects such functions, aiming to fulfill the following criteria: code clarity over performance (i.e. plain R code instead of C code), most important analysis steps over completeness (analysis 'by hand', not automated integration etc.), emphasis on quantitative visualization (intensity-coded color scale, etc.).
Version: | 0.1.0 |
Imports: | ggplot2, Matrix, scales, assertthat, dplyr, viridis, viridisLite, methods |
Suggests: | testthat, tibble |
Published: | 2020-06-25 |
Author: | Felix Frauhammer [aut, cre], Simon Anders [ctb] (Simon Anders wrote the colVars_spm function.) |
Maintainer: | Felix Frauhammer <felixwertek at gmail.com> |
License: | GPL-3 |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | scUtils results |
Reference manual: | scUtils.pdf |
Package source: | scUtils_0.1.0.tar.gz |
Windows binaries: | r-devel: scUtils_0.1.0.zip, r-release: scUtils_0.1.0.zip, r-oldrel: scUtils_0.1.0.zip |
macOS binaries: | r-release: scUtils_0.1.0.tgz, r-oldrel: scUtils_0.1.0.tgz |
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