cellular: Agents to stimulate cellular differentiation

In glmtoolbox: Set of Tools to Data Analysis using Generalized Linear Models

Agents to stimulate cellular differentiation

Description

In a biomedical study of the immuno-activating ability of two agents, TNF (tumor necrosis factor) and IFN (interferon), to induce cell differentiation, the number of cells that exhibited markers of differentiation after exposure to TNF and IFN was recorded. At each of the 16 TNF/INF dose combinations, 200 cells were examined. The main question is whether the two agents stimulate cell differentiation synergistically or independently.

Usage

data(cellular)

Format

A data frame with 16 rows and 3 variables:

cells

a numeric vector giving the number of cells that exhibited markers of differentiation after exposure to the dose of the two agents

tnf

a numeric vector giving the dose (U/ml) of TNF

ifn

a numeric vector giving the dose (U/ml) of IFN

References

Piegorsch W.W., Weinberg C.R., Margolin B.H. (1988) Exploring simple independent action in multifactor tables of proportions. Biometrics 44:595-603.

Vanegas L.H., Rondon L.M. (2020) A data transformation to deal with constant under/over-dispersion in binomial and poisson regression models. Journal of Statistical Computation and Simulation 90:1811-1833.

Examples

data(cellular)
dev.new()
barplot(100*cells/200 ~ ifn + tnf, beside=TRUE, data=cellular, col=terrain.colors(4),
        xlab="Dose of TNF", ylab="% of cells with markers of differentiation")
legend("topleft", legend=c("0","4","20","100"), fill=terrain.colors(4),
       title="Dose of IFN", bty="n")

glmtoolbox documentation built on Sept. 11, 2024, 7:32 p.m.