Create a grofit.control object. — growth.control • QurvE

A grofit.control object is required to perform various computations on growth data stored within grodata objects (created with read_data or parse_data). A grofit.control object is created automatically as part of growth.workflow.

Usage

growth.control(
  neg.nan.act = FALSE,
  clean.bootstrap = TRUE,
  suppress.messages = FALSE,
  fit.opt = c("a"),
  t0 = 0,
  tmax = NA,
  min.growth = NA,
  max.growth = NA,
  log.x.gc = FALSE,
  log.y.lin = TRUE,
  log.y.spline = TRUE,
  log.y.model = TRUE,
  lin.h = NULL,
  lin.R2 = 0.97,
  lin.RSD = 0.1,
  lin.dY = 0.05,
  biphasic = FALSE,
  interactive = FALSE,
  nboot.gc = 0,
  smooth.gc = 0.55,
  model.type = c("logistic", "richards", "gompertz", "gompertz.exp", "huang", "baranyi"),
  dr.method = c("model", "spline"),
  dr.model = c("gammadr", "multi2", "LL.2", "LL.3", "LL.4", "LL.5", "W1.2", "W1.3",
    "W1.4", "W2.2", "W2.3", "W2.4", "LL.3u", "LL2.2", "LL2.3", "LL2.3u", "LL2.4",
    "LL2.5", "AR.2", "AR.3", "MM.2"),
  dr.have.atleast = 6,
  dr.parameter = c("mu.linfit", "lambda.linfit", "dY.linfit", "A.linfit", "mu.spline",
    "lambda.spline", "dY.spline", "A.spline", "mu.model", "lambda.model",
    "dY.orig.model", "A.orig.model"),
  smooth.dr = NULL,
  log.x.dr = FALSE,
  log.y.dr = FALSE,
  nboot.dr = 0,
  growth.thresh = 1.5
)

Arguments

neg.nan.act: (Logical) Indicates whether the program should stop when negative growth values or NA values appear (TRUE). Otherwise, the program removes these 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 whether 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 throughput data. Note: warnings are still displayed. Default: FALSE.
fit.opt: (Character or character vector) Indicates whether the program should perform a linear regression ('l'), model fit ('m'), spline fit ('s'), or all ('a'). Combinations can be freely chosen by providing a character vector, e.g. fit.opt = c('l', 's') Default: fit.opt = c('l', 's').
t0: (Numeric) Minimum time value considered for linear and spline fits.
tmax: (Numeric) Maximum time value considered for linear and spline fits.
min.growth: (Numeric) Indicate whether only growth values above a certain threshold should be considered for linear regressions or spline fits.
max.growth: (Numeric) Indicate whether only growth values below a certain threshold should be considered for linear regressions or spline fits.
log.x.gc: (Logical) Indicates whether ln(x+1) should be applied to the time data for linear and spline fits. Default: FALSE.
log.y.lin: (Logical) Indicates whether ln(y/y0) should be applied to the growth data for linear fits. Default: TRUE
log.y.spline: (Logical) Indicates whether ln(y/y0) should be applied to the growth data for spline fits. Default: TRUE
log.y.model: (Logical) Indicates whether ln(y/y0) should be applied to the growth data for model fits. Default: TRUE
lin.h: (Numeric) Manually define the size of the sliding window used in growth.gcFitLinear If NULL, h is calculated for each samples based on the number of measurements in the growth phase of the plot.
lin.R2: (Numeric) R² threshold for growth.gcFitLinear
lin.RSD: (Numeric) Relative standard deviation (RSD) threshold for the calculated slope in growth.gcFitLinear
lin.dY: (Numeric) Threshold for the minimum fraction of growth increase a linear regression window should cover. Default: 0.05 (5%).
biphasic: (Logical) Shall growth.gcFitLinear and growth.gcFitSpline try to extract growth parameters for two different growth phases (as observed with, e.g., diauxic shifts) (TRUE) or not (FALSE)?
interactive: (Logical) Controls whether the fit of each growth curve and method is controlled manually by the user. If TRUE, each fit is visualized in the Plots pane and the user can adjust fitting parameters and confirm the reliability of each fit per sample. Default: TRUE.
nboot.gc: (Numeric) Number of bootstrap samples used for nonparametric growth curve fitting with growth.gcBootSpline. Use nboot.gc = 0 to disable the bootstrap. Default: 0
smooth.gc: (Numeric) Parameter describing the smoothness of the spline fit; usually (not necessary) within (0;1]. smooth.gc=NULL causes the program to query an optimal value via cross validation techniques. Especially for datasets with few data points the option NULL might cause a too small smoothing parameter. This can result a too tight fit that is susceptible to measurement errors (thus overestimating growth rates) or produce an error in smooth.spline or lead to overfitting. The usage of a fixed value is recommended for reproducible results across samples. See smooth.spline for further details. Default: 0.55
model.type: (Character) Vector providing the names of the parametric models which should be fitted to the data. Default: c('logistic', 'richards', 'gompertz', 'gompertz.exp', 'huang', 'baranyi').
dr.method: (Character) Define the method used to perform a dose-responde analysis: smooth spline fit ('spline') or model fitting ('model').
dr.model: (Character) Provide a list of models from the R package 'drc' to include in the dose-response analysis (if dr.method = 'model'). If more than one model is provided, the best-fitting model will be chosen based on the Akaike Information Criterion.
dr.have.atleast: (Numeric) Minimum number of different values for the response parameter one should have for estimating a dose response curve. Note: All fit procedures require at least six unique values. Default: 6.
dr.parameter: (Character or numeric) The response parameter in the output table to be used for creating a dose response curve. See growth.drFit for further details. Default: 'mu.linfit', which represents the maximum slope of the linear regression. Typical options include: 'mu.linfit', 'lambda.linfit', 'dY.linfit', 'mu.spline', 'dY.spline', 'mu.model', and 'A.model'.
smooth.dr: (Numeric) Smoothing parameter used in the spline fit by smooth.spline during dose response curve estimation. Usually (not necessesary) in (0; 1]. See smooth.spline for further details. Default: NULL.
log.x.dr: (Logical) Indicates whether ln(x+1) should be applied to the concentration data of the dose response curves. Default: FALSE.
log.y.dr: (Logical) Indicates whether ln(y+1) should be applied to the response data of the dose response curves. Default: FALSE.
nboot.dr: (Numeric) Defines the number of bootstrap samples for EC50 estimation. Use nboot.dr = 0 to disable bootstrapping. Default: 0.
growth.thresh: (Numeric) Define a threshold for growth. Only if any growth value in a sample is greater than growth.thresh (default: 1.5) times the start growth, further computations are performed. Else, a message is returned.

Value

Generates a list with all arguments described above as entries.

References

Matthias Kahm, Guido Hasenbrink, Hella Lichtenberg-Frate, Jost Ludwig, Maik Kschischo (2010). grofit: Fitting Biological Growth Curves with R. Journal of Statistical Software, 33(7), 1-21. DOI: 10.18637/jss.v033.i07

Examples

# default option
control_default <- growth.control()
# user defined
control_manual <- growth.control(fit.opt = c('s', 'm'),
                                 smooth.gc = 0.5,
                                 model.type = c('huang', 'baranyi'))