Multiple.singlefit: Multiple.singlefit

In Michorlab/ACESO: A Cancer Evolution Simulation Optimizer

Description

Multiple concentration-response fit

Usage

Multiple.singlefit(data, resp = "Birth_rate", conc = "CONC",
  fct = drc::LL.4(), linear.model = FALSE, log.x = FALSE, ...)

Arguments

data	Concentration-response dataframe.
resp	Response to be fitted (Y axis). Default is Birth_rate.
conc	Name of the column with the drug concentration values.
fct	nonlinear function. Currently available functions can be found in drc package (use getMeanFunctions for a full list). By default the four-parameter log-logistic model LL.4 is used. More examples include the three- and five-parameter log-logistic models LL.3, LL.5,the Weibull model W1.4, etc.
linear.model	logical value indicating whether the curve should be fitted using a linear model. If TRUE, the fct argument is ignored. FALSE by default.
log.x	logical. Logaritmically transform x axis values? FALSE by default.
...	Additional arguments for the model fitting function. See drm for more info.

Value

This function returns the coefficient estimates of the fitted model and the corresponding plots for each cell line.

Examples

## Not run: 
#Effect of Alvocidib on the cell counts of BT-20 and MCF7 cell lines.

filename=system.file("extdata","2cell_lines.txt",package="ACESO")

growth_data=read.cellcount.data(filename,sep="\t")

#Calculate net growth rate assuming an exponential growth of the cells:
growth_data<-net_growth_rate(growth_data)

#Fit the data with a 4 parameter log-logistic function:
Multiple.singlefit(growth_data,resp="Net_growth",conc="CONC",fct=drc::LL.4())

Multiple.singlefit(growth_data,resp="Net_growth",conc="CONC",fct=drc::LL.4(),log.x=T)

## End(Not run)

Michorlab/ACESO documentation built on June 4, 2021, 4:57 p.m.