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 (sigmoidal, double sigmoidal, no signal or ambiguous) best describes the data. No signal means the intensity does not reach a high enough point or does not change at all over time. Sigmoidal means intensity starts from a small number than climbs to a maximum. Double sigmoidal means intensity starts from a small number, climbs to a maximum then starts to decay. After the decision between those four options, the algorithm gives the sigmoidal (or double sigmoidal) associated parameter values that quantifies the time intensity curve. The origin of the package name came from "SIngle CEll Growth Analysis in R".

Version: 0.2
Imports: dplyr, minpack.lm, fBasics, ggplot2, cowplot, stats
Suggests: knitr
Published: 2017-07-11
Author: M. Umut Caglar [aut, cre], Claus O. Wilke [aut]
Maintainer: M. Umut Caglar <umut.caglar at gmail.com>
BugReports: https://github.com/wilkelab/sicegar/issues
License: GPL-2 | GPL-3
URL: https://github.com/wilkelab/sicegar
NeedsCompilation: no
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.tar.gz
Windows binaries: r-devel: sicegar_0.2.zip, r-release: sicegar_0.2.zip, r-oldrel: sicegar_0.2.zip
OS X El Capitan binaries: r-release: sicegar_0.2.tgz
OS X Mavericks binaries: r-oldrel: sicegar_0.2.tgz
Old sources: sicegar archive

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