sicegar: Analysis of Single-Cell Viral Growth Curves

Aims to quantify time intensity data by using sigmoidal and double sigmoidal curves. It fits straight lines, sigmoidal, and double sigmoidal curves on to time vs intensity data. Then all the fits are used to make decision on which model best describes the data. This method was first developed in the context of single-cell viral growth analysis (for details, see Caglar et al. (2018) <doi:10.7717/peerj.4251>), and the package name stands for "SIngle CEll Growth Analysis in R".

Version:	0.2.4
Imports:	dplyr, minpack.lm, fBasics, ggplot2, stats
Suggests:	covr, cowplot, testthat, knitr, rmarkdown
Published:	2021-05-08
DOI:	10.32614/CRAN.package.sicegar
Author:	M. Umut Caglar [aut], Claus O. Wilke [aut, cre]
Maintainer:	Claus O. Wilke <wilke at austin.utexas.edu>
BugReports:	https://github.com/wilkelab/sicegar/issues
License:	GPL-2 | GPL-3
URL:	https://github.com/wilkelab/sicegar
NeedsCompilation:	no
Citation:	sicegar citation info
Materials:	README
CRAN checks:	sicegar results

Documentation:

Reference manual:	sicegar.pdf
Vignettes:	Calculation of additional parameters of interest Identifying the best-fitting model category Fitting individual models Introduction Plotting the fitted models

Downloads:

Package source:	sicegar_0.2.4.tar.gz
Windows binaries:	r-devel: sicegar_0.2.4.zip, r-release: sicegar_0.2.4.zip, r-oldrel: sicegar_0.2.4.zip
macOS binaries:	r-release (arm64): sicegar_0.2.4.tgz, r-oldrel (arm64): sicegar_0.2.4.tgz, r-release (x86_64): sicegar_0.2.4.tgz, r-oldrel (x86_64): sicegar_0.2.4.tgz
Old sources:	sicegar archive

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