| cellsurvLQfit {CFAssay} | R Documentation |
This function calculates the linear coefficient alpha and the coefficient beta of the dose-squared term (see manual for this R-package) for colony counts measured for a set of irradiation doses and repeated experiments. The function is a wrapper for the R-functions glm or lm, which simplifies use of these functions for cell survival data.
cellsurvLQfit(X, method="ml", PEmethod="fit")
X |
A data frame which contains at least columns |
method |
Determines the method used for the fit. |
PEmethod |
Controls the value of the plating efficiencies, i.e. the colony counts for untreated cells. |
In the data frame X, Exp identifies the experimental replicates and may be numeric or non-numeric. method="ml" uses R function glm with quasipoisson family and link function "log". method="ls" uses R function lm. PEmethod="fit" fits plating efficiencies for every experiments. PEmethod="fix" uses observed plating efficiencies. If there is no 0-value in the dose-column, PEmethod is overwritten with "fix" and X has to contain a further column pe containing the plating efficiencies, i.e. ncolonies/ncells from untreated cells, not per hundred or percent.
The function returns an object of class cellsurvLQfit, which is similar to classes glm or lm, however containing two additional entries, type and PEmethod, which are used for printing and plotting. The full result is returned invisibly, i.e. the function has to be used with print or plot or assigned to a variable, say for e.g. fit as in the example below.
Herbert Braselmann
Franken NAP, Rodermond HM, Stap J, et al. Clonogenic assay of cells in vitro. Nature Protoc 2006;1:2315-19.
glm and family with references for generalized linear modelling, lm
datatab<- read.table(system.file("doc", "expl1_cellsurvcurves.txt", package="CFAssay"), header=TRUE, sep="\t")
X<- subset(datatab, cline=="okf6TERT1")
fit<- cellsurvLQfit(X) #using default options
print(fit)
print(fit$type)
print(fit$PEmethod)
#Using other options:
print(cellsurvLQfit(X, method="ls"))
print(cellsurvLQfit(X, PEmethod="fix"))
print(cellsurvLQfit(X, method="ls", PEmethod="fix"))
print(cellsurvLQfit(X, method="franken"))