The function does an ANOVA of cell survival data from experimental 2-way designs where a treatment factor is tested on a control and on an altered cell line or where two different simultaneous treatments are tested on cells from a common unaltered clone. The function is a wrapper for the R-function
glm. quasipoisson family is used with link function
"log", i.e. dependency of treatment factors is considered as logarithmically additive.
cfa2way(X, A, B, param="A/B", method="ml")
a data frame which contains columns
a character string containing the name of a treatment or cell line variable (first factor in the model)
a character string containing the name of a treatment or cell line variable (second factor in the model)
Controls the parametrization of the model. Options are "A/B" for B nested in A , "B/A" for A nested in B and "A*B" for interaction term.
determines the method used for the fit.
In the data frame
Exp identifies the experimental replicates and may be numeric or non-numeric. The two treatment or cell line columns should have numeric values 0, 1, ... for 2, 3, ... levels. For e.g. if a column describes clonal alteration (transfection, knock-down etc.) by a gene then 0 means unaltered or control and 1 means altered. Similar if a column describes treatment with one dose then 0 means untreated and 1 treated. 2 would indicate another dose level from the same treatment drug without taking it as a continuous covariate as for cell survival curves for radiation.
The function returns an object of class
cfa2way containing three elements,
fit2 are objects of class
method="ml" or of class
fit1 has logarithmic additive parameters without interaction.
fit2 has logarithmic additive parameters and interaction.
anv is of class
anova and contains the F-test. The full result is returned invisibly, i.e. the function has to be used with
fitcomp as in the example below.
1 2 3 4 5
datatab<- read.table(system.file("doc", "exp2_2waycfa.txt", package="CFAssay"), header=TRUE, sep="\t") names(datatab) # has columns "x5fuCis" and "siRNA" fitcomp<- cfa2way(datatab, A="siRNA", B="x5fuCis", param="A/B") print(fitcomp, labels=c(A="siRNA",B="x5fuCis")) print(cfa2way(datatab, A="siRNA", B="x5fuCis", param="A/B", method="ls"))
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