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
Author: M. Umut Caglar [aut], Claus O. Wilke ORCID iD [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

Downloads:

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
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-release (x86_64): sicegar_0.2.4.tgz, r-oldrel: sicegar_0.2.4.tgz
Old sources: sicegar archive

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