Create a fl.control object. — fl.control • QurvE

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

Usage

fl.control(
  fit.opt = c("l", "s"),
  x_type = c("growth", "time"),
  norm_fl = TRUE,
  t0 = 0,
  tmax = NA,
  min.growth = NA,
  max.growth = NA,
  log.x.lin = FALSE,
  log.x.spline = FALSE,
  log.y.lin = FALSE,
  log.y.spline = FALSE,
  lin.h = NULL,
  lin.R2 = 0.97,
  lin.RSD = 0.05,
  lin.dY = 0.05,
  dr.parameter = "max_slope.spline",
  dr.method = c("model", "spline"),
  dr.have.atleast = 5,
  smooth.dr = NULL,
  log.x.dr = FALSE,
  log.y.dr = FALSE,
  nboot.dr = 0,
  biphasic = FALSE,
  interactive = FALSE,
  nboot.fl = 0,
  smooth.fl = 0.75,
  growth.thresh = 1.5,
  suppress.messages = FALSE,
  neg.nan.act = FALSE,
  clean.bootstrap = TRUE
)

Arguments

fit.opt: (Character or vector of strings) Indicates whether the program should perform a linear regression ('l') and/or spline fit ('s'). Default: fit.opt = c('l', 's').
x_type: (Character) Which data type shall be used as independent variable? Options are 'growth' and 'time'.
norm_fl: (Logical) use normalized (to growth) fluorescence data in fits. Has an effect only when x_type = 'time'
t0: (Numeric) Minimum time value considered for linear and spline fits (if x_type = 'time').
tmax: (Numeric) Maximum time value considered for linear and spline fits (if x_type = 'time')..
min.growth: (Numeric) Indicate whether only values above a certain threshold should be considered for linear regressions or spline fits (if x_type = 'growth').
max.growth: (Numeric) Indicate whether only growth values below a certain threshold should be considered for linear regressions or spline fits (if x_type = 'growth').
log.x.lin: (Logical) Indicates whether ln(x+1) should be applied to the independent variable for linear fits. Default: FALSE.
log.x.spline: (Logical) Indicates whether ln(x+1) should be applied to the independent variable for spline fits. Default: FALSE.
log.y.lin: (Logical) Indicates whether ln(y/y0) should be applied to the fluorescence data for linear fits. Default: FALSE
log.y.spline: (Logical) Indicates whether ln(y/y0) should be applied to the fluorescence data for spline fits. Default: FALSE
lin.h: (Numeric) Manually define the size of the sliding window used in flFitLinear. If NULL, h is calculated for each samples based on the number of measurements in the fluorescence increase phase of the plot.
lin.R2: (Numeric) R² threshold for flFitLinear.
lin.RSD: (Numeric) Relative standard deviation (RSD) threshold for the calculated slope in flFitLinear.
lin.dY: (Numeric) Threshold for the minimum fraction of growth increase a linear regression window should cover. Default: 0.05 (5%).
dr.parameter: (Character or numeric) The response parameter in the output table to be used for creating a dose response curve. See fl.drFit for further details. Default: 'max_slope.spline', which represents the maximum slope of the spline fit Typical options include: 'max_slope.linfit', 'dY.linfit', 'max_slope.spline', and 'dY.spline'.
dr.method: (Character) Perform either a smooth spline fit on response parameter vs. concentration data ('spline') or fit a biosensor response model with 'model' (proposed by Meyer et al., 2019).
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.
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.
biphasic: (Logical) Shall flFitLinear and flFitSpline try to extract fluorescence parameters for two different phases (as observed with, e.g., regulator-promoter systems with varying response in different growth stages) (TRUE) or not (FALSE)?
interactive: (Logical) Controls whether the fit for each sample 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.fl: (Numeric) Number of bootstrap samples used for nonparametric curve fitting with flBootSpline. Use nboot.fl = 0 to disable the bootstrap. Default: 0
smooth.fl: (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 slopes) 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
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.
suppress.messages: (Logical) Indicates whether messages (information about current fluorescence curve, EC50 values etc.) should be displayed (FALSE) or not (TRUE). This option is meant to speed up the high-throughput processing data. Note: warnings are still displayed. Default: FALSE.
neg.nan.act: (Logical) Indicates whether the program should stop when negative fluorescence 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.

Value

Generates a list with all arguments described above as entries.

References

Meyer, A.J., Segall-Shapiro, T.H., Glassey, E. et al. Escherichia coli “Marionette” strains with 12 highly optimized small-molecule sensors. Nat Chem Biol 15, 196–204 (2019). DOI: 10.1038/s41589-018-0168-3

Examples

# default option
control_default <- fl.control()
# user defined
control_manual <- fl.control(fit.opt = c('s'),
                             smooth.fl = 0.6,
                             x_type = 'time',
                             t0 = 2)