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

View source: R/cellsurvLQfit.R

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.

1 | ```
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`

1 2 3 4 5 6 7 8 9 10 11 | ```
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"))
``` |

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