cfa2way: Two-way analysis for cell survival data
In ZytoHMGU/CFAssay: Statistical analysis for the Colony Formation Assay

Description Usage Arguments Details Value Author(s) See Also Examples

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.

1	cfa2way(X, A, B, param="A/B", method="ml")

`X`	a data frame which contains columns `Exp, ncells, ncolonies` and two further columns for the treatment variables, see details.
`A`	a character string containing the name of a treatment or cell line variable (first factor in the model)
`B`	a character string containing the name of a treatment or cell line variable (second factor in the model)
`param`	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.
`method`	determines the method used for the fit. `"ml"` is for maximum-likelihood, `"ls"` for least-squares.

In the data frame X, 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, fit1, fit2 and anv. fit1 and fit2 are objects of class glm when method="ml" or of class lm when method="ls". 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 print or assigned to a variable, say for e.g. fitcomp as in the example below.

Herbert Braselmann

glm and family with references for generalized linear modelling.

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"))