grofit (version 1.1.1-1)

grofit.control: Function to set all available grofit options

Description

The function generates an object of class grofit.control with the different grofit options and also allows to change these options.

Usage

grofit.control(neg.nan.act = FALSE, clean.bootstrap = TRUE, suppress.messages = FALSE, fit.opt = "b", log.x.gc = FALSE, log.y.gc = FALSE, interactive = TRUE, nboot.gc = 0, smooth.gc= NULL, model.type=c("logistic", "richards","gompertz", "gompertz.exp"), have.atleast = 6, parameter = 9, smooth.dr = NULL, log.x.dr = FALSE, log.y.dr = FALSE, nboot.dr = 0)

Arguments

neg.nan.act

Logical, indicates wether the program should stop when negative growth values or NA values appear (TRUE). Otherwise the program removes this values silently (FALSE). Improper values may be caused by incorrect data or input errors. Default: FALSE.

clean.bootstrap

Logical, determines if negative values which occur during bootstrap should be removed (TRUE) or kept (FALSE). Note: Infinite values are always removed. Default: TRUE.

suppress.messages

Logical, indicates wether grofit messages (information about current growth curve, EC50 values etc.) should be displayed (FALSE) or not (TRUE). This option is meant to speed up the processing of high throuput data. Note: warnings are still displayed. Default: FALSE.

fit.opt

Indicates wether the program should perform a model fit ("m"), a spline fit ("s") or both ("b"). Default: "b".

log.x.gc

Logical, indicates wether a $ln(x+1)$ should be applied to the time data of the growth curves. Default: FALSE.

log.y.gc

Logical, indicates wether a $ln(y+1)$ should be applied to the growth data of the growth curves. Default: FALSE.

interactive

Logical, controls whether the fit of each growth curve is controlled manually by the user. Default: TRUE.

nboot.gc

Number of bootstrap samples used for the model free growth curve fitting. Use nboot.gc=0 to disable the bootstrap. Default: 0.

smooth.gc

Parameter describing the smoothness of the spline fit; usually (not necessary) in (0;1]. Set smooth.gc=NULL causes the program to query an optimal value via cross validation techniques. Note: This is partly experimental. In future improved implementations of the smooth.spline function may lead to different results. See documentation of the R function smooth.spline for further details. Especially for datasets with few data points the option NULL might result in a too small smoothing parameter, which produces an error in smooth.spline. In that case the usage of a fixed value is recommended. Default: NULL.

model.type

Character vector giving the names of the parametric models which should be fitted to the data. Default: c("gompertz", "logistic", "gompertz.exp", "richards").

have.atleast

Minimum number of different values for the response parameter one shoud have for estimating a dose response curve. Note: All fit procedures require at least six unique values. Default: 6.

parameter

The column of the output table which should be used for creating a dose response curve. See documentation of gcFit, drFit or summary.gcFit for further details. Default: 9, which represents the maximum slope of the parametric growth curve fit.

smooth.dr

Smoothing parameter used in the spline fit by smooth.spline during dose response curve estimation. Usually (not necessesary) in (0; 1]. See documentation of smooth.spline for further details. Default: NULL.

log.x.dr

Logical, indicates wether a $ln(x+1)$ should be applied to the concentration data of the dose response curves. Default: FALSE.

log.y.dr

Logical, indicates wether a $ln(y+1)$ should be applied to the response data of the dose response curves. Default: FALSE.

nboot.dr

Numeric value, defining the number of bootstrap samples for EC50 estimation. Use nboot.dr=0 to disable bootstrapping. Default: 0.

Value

Generates a list containing the entrys described above.

Examples

# default option
DefOpt <- grofit.control()
# user defined
MyOpt <- grofit.control(smooth.gc=0.5, model.type=c("gompertz", "logistic"))