sfpmean: Pointwise mean survival fractions for curves with several...

In CFAssay: Statistical analysis for the Colony Formation Assay

Description

The function calculates mean survival fractions for curves averaged over experimental replicates. The function is employed by function plot.cellsurvLQfit for plotting observed means

Usage

sfpmean(X, S0=NULL)

Arguments

X	A data frame which contains columns Exp, dose, ncells, ncolonies and if S0=NULL, X has to contain a further column pe for plating efficiencies.
S0	If not NULL, a named numerical vector of length equal to the number of different experiments, i.e. length(S0)==length(unique(X$Exp)) has to be TRUE. Default is S0=NULL, i.e. undefined.

Details

In the data frame X, Exp identifies the experimental replicates and may be numeric or non-numeric. S0 may contain plating efficiencies for each replicate, resulting from function pes or from cellsurvLQfit (fitted). When S0=NULL, X must have a column with name pe, containing the plating efficiencies.

Value

A numerical matrix with two rows, the first row containing the survival fractions for each radiation dose, second row the standard deviations.

Author(s)

Herbert Braselmann

See Also

pes, cellsurvLQfit, plot.cellsurvLQfit

Examples

datatab <- read.table(system.file("doc", "expl1_cellsurvcurves.txt", package="CFAssay"), header=TRUE, sep="\t")
X <- subset(datatab, cline=="okf6TERT1")
## S0 from data with fucntion pes
S0 <- pes(X)$pe  #observed plating efficiencies
length(S0)==length(unique(X$Exp)) #length ok?
names(S0) <- pes(X)$Exp
sfpmean(X, S0)
## Not run: 
## S0 from LQ model fit
fit <- cellsurvLQfit(X)
fit$coef  #contains fitted log-pe
grep("Exp",names(fit$coef))
S01 <- exp(fit$coef[1:8])  #fitted pe
sfpmean(X, S01) #names of S01 still to adjust!

## End(Not run)
## Not run: sfpmean(X)  #yields an error for this data set

Example output

[1] TRUE
         dose_0     dose_1     dose_2     dose_3     dose_4      dose_6
SF    1.0900000 0.63666667 0.38800000 0.19625000 0.10933333 0.025905068
stdev 0.1036205 0.04606754 0.06697965 0.02401148 0.03161806 0.003750415
method = ml 
PEmethod = fit 
       dose       dose2 
-0.51937898 -0.02102614 
Use 'print' to see detailed results 

factor(Exp)e1 factor(Exp)e2 factor(Exp)e3 factor(Exp)e4 factor(Exp)e5 
  -1.60668602   -1.69334624   -2.01037651   -1.86922792   -2.05240465 
factor(Exp)e6 factor(Exp)e7 factor(Exp)e8          dose         dose2 
  -2.21965387   -2.43463411   -2.10907991   -0.51937898   -0.02102614 
[1] 1 2 3 4 5 6 7 8
         dose_0     dose_1     dose_2      dose_3      dose_4      dose_6
SF    0.9975485 0.57571283 0.33340514 0.178369394 0.085193618 0.021081745
stdev 0.1074320 0.03476128 0.01534523 0.009429196 0.007655484 0.002530412

CFAssay documentation built on Nov. 8, 2020, 11:10 p.m.