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Generic plot function for drFitFL objects.

Source: R/fluorescence_plots.R
plot.drFitfl.Rd

codedrFitfl calls plot.drFitFLModel for each group used in a dose-response analysis with dr.method = "model"

Usage

# S3 method for drFitfl
plot(
  x,
  ec50line = TRUE,
  log = c("xy"),
  pch = 1,
  broken = TRUE,
  bp,
  n.xbreaks,
  n.ybreaks,
  colSpline = 1,
  colData = 1,
  cex.point = 1,
  cex.lab = 1.5,
  cex.axis = 1.3,
  y.lim = NULL,
  x.lim = NULL,
  lwd = 2,
  plot = TRUE,
  export = FALSE,
  height = 7,
  width = 9,
  out.dir = NULL,
  ...
)

Arguments

x

object of class drFit, created with growth.drFit.

ec50line

(Logical) Show pointed horizontal and vertical lines at the EC50 values (TRUE) or not (FALSE).

log

(Character) String which contains '"x"' if the x axis is to be logarithmic, '"y"' if the y axis is to be logarithmic and '"xy"' or '"yx"' if both axes are to be logarithmic. The default is "x". The empty string "" yields the original axes.

pch

(Numeric) Shape of the raw data symbols.

broken

(Logical) If TRUE the x axis is broken provided this axis is logarithmic (using functionality in the CRAN package 'plotrix').

bp

(Numeric) Specifying the break point below which the dose is zero (the amount of stretching on the dose axis above zero in order to create the visual illusion of a logarithmic scale including 0). The default is the base-10 value corresponding to the rounded value of the minimum of the log10 values of all positive dose values. This argument is only working for logarithmic dose axes.

n.xbreaks

(Numeric) Number of breaks on the x-axis (if not log-transformed). The breaks are generated using pretty. Thus, the final number of breaks can deviate from the user input.

n.ybreaks

(Numeric) Number of breaks on the y-axis (if not log-transformed). The breaks are generated using pretty. Thus, the final number of breaks can deviate from the user input.

colSpline

(Numeric or character) Spline line colour.

colData

(Numeric or character) Contour color of the raw data circles.

cex.point

(Numeric) Size of the raw data points.

cex.lab

(Numeric) Font size of axis titles.

cex.axis

(Numeric) Font size of axis annotations.

y.lim

(Numeric vector with two elements) Optional: Provide the lower (l) and upper (u) bounds on the y-axis as a vector in the form c(l, u). If only the lower or upper bound should be fixed, provide c(l, NA) or c(NA, u), respectively.

x.lim

(Numeric vector with two elements) Optional: Provide the lower (l) and upper (u) bounds on the x-axis as a vector in the form c(l, u). If only the lower or upper bound should be fixed, provide c(l, NA) or c(NA, u), respectively.

lwd

(Numeric) Line width of the individual splines.

plot

(Logical) Show the generated plot in the Plots pane (TRUE) or not (FALSE).

export

(Logical) Export the generated plot as PDF and PNG files (TRUE) or not (FALSE).

height

(Numeric) Height of the exported image in inches.

width

(Numeric) Width of the exported image in inches.

out.dir

(Character) Name or path to a folder in which the exported files are stored. If NULL, a "Plots" folder is created in the current working directory to store the files in.

...

Additional arguments. This has currently no effect and is only meant to fulfill the requirements of a generic function.

Value

One plot per condition tested in the dose-response analysis (fl.drFit with control = fl.control(dr.method = "model")).

Examples

# load example dataset
input <- read_data(data.growth = system.file("lac_promoters.xlsx", package = "QurvE"),
                   data.fl = system.file("lac_promoters.xlsx", package = "QurvE"),
                   sheet.growth = 1,
                   sheet.fl = 2 )
#> Sample data are stored in columns. If they are stored in row format, please run read_data() with data.format = 'row'.

# Define fit controls
control <- fl.control(fit.opt = "s",
             x_type = "time", norm_fl = TRUE,
             dr.parameter = "max_slope.spline",
             dr.method = "model",
             suppress.messages = TRUE)

# Run curve fitting workflow
res <- flFit(fl_data = input$norm.fluorescence,
             time = input$time,
             parallelize = FALSE,
             control = control)

# Perform dose-response analysis with biosensor model
drFitfl <- fl.drFit(flTable = res$flTable, control = control)

plot(drFitfl)