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R package sicegar

Originally written by M. Umut Caglar and Claus O. Wilke. Updates and current maintenance by Johanna Hardin, Sam Butler, Phineus Choi, Thomas Matheis, and Mira Terdiman.

This package aims to quantify time intensity data by using sigmoidal and double sigmoidal curves. It fits sigmoidal and double sigmoidal curves on to time vs intensity data. Then both fits are used to make a 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. Once the decision has been reached, the algorithm returns the parameters associated with the sigmoidal or double-sigmoidal model quantifying the time-intensity curve.

The package name stands for "SIngle CEll Growth Analysis in R".

CRAN: https://cran.r-project.org/package=sicegar/

Source: https://github.com/hardin47/sicegar/

Vignettes: https://hardin47.github.io/sicegar/

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Install

install.packages('sicegar')

Monthly Downloads

321

Version

0.3.0

License

GPL-2 | GPL-3

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Maintainer

Jo Hardin

Last Published

November 15th, 2025

Functions in sicegar (0.3.0)

sigmoidalFitFormula_h0

sigmoidalFitFormula_h0
unnormalizeData

Unnormalization of given data
parameterCalculation_h0

additional parameter calculation with help of fits
doublesigmoidalFitFunction

Double sigmoidal fit function with h0.
doublesigmoidalFitFormula_h0

Double Sigmoidal Formula with h0
categorize_h0

Categorize input data by comparing the AIC values of the three fitted models.
figureModelCurves

Generate model associated figures.
doublesigmoidalFitFormula

Double Sigmoidal Formula
multipleFitFunction

multiple fit function.
categorize

Categorize input data by comparing the AIC values of the three fitted models.
fitAndCategorize

Fit and categorize.
dataCheck

Checks if data is in correct format.
doublesigmoidalFitFunction_h0

Double sigmoidal fit function with h0.
multipleFitFunction_h0

multiple fit function h0.
preCategorize

Checks for signal in the data.
sigmoidalFitFunction

Sigmoidal fit function
normalizeData

Normalization of given data
sigmoidalFitFormula

sigmoidalFitFormula
sameSourceDataCheck

Check that data came from the same source.
parameterCalculation

additional parameter calculation with help of fits
sigmoidalFitFunction_h0

Sigmoidal fit function with h0 estimation