plot.flFitSpline {QurvE}

Generic plot function for flFitSpline objects.

Description

plot.flFitSpline generates the spline fit plot for a single sample.

Usage

## S3 method for class 'flFitSpline'
plot(
  x,
  add = FALSE,
  raw = TRUE,
  slope = TRUE,
  deriv = TRUE,
  spline = TRUE,
  log.y = FALSE,
  basesize = 16,
  pch = 1,
  colData = 1,
  colSpline = "dodgerblue3",
  cex.point = 2,
  lwd = 0.7,
  y.lim = NULL,
  x.lim = NULL,
  y.lim.deriv = NULL,
  n.ybreaks = 6,
  y.title = NULL,
  x.title = NULL,
  y.title.deriv = NULL,
  plot = TRUE,
  export = FALSE,
  width = 8,
  height = ifelse(deriv == TRUE, 8, 6),
  out.dir = NULL,
  ...
)

Arguments

x

Object of class flFitSpline, created with flFitSpline.

add

(Logical) Shall the fitted spline be added to an existing plot? TRUE is used internally by plot.flBootSpline.

raw

(Logical) Display raw growth as circles (TRUE) or not (FALSE).

slope

(Logical) Show the slope at the maximum slope (TRUE) or not (FALSE).

deriv

(Logical) Show the derivative (i.e., slope) over time in a secondary plot (TRUE) or not (FALSE).

spline

(Logical) Only for add = TRUE: add the current spline to the existing plot (FALSE).

log.y

(Logical) Log-transform the y-axis (TRUE) or not (FALSE).

basesize

(Numeric) Base font size.

pch

(Numeric) Symbol used to plot data points.

colData

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

colSpline

(Numeric or character) Spline line colour.

cex.point

(Numeric) Size of the raw data points.

lwd

(Numeric) Spline line width.

y.lim

(Numeric vector with two elements) Optional: Provide the lower (l) and upper (u) bounds on y-axis of the fluorescence curve plot 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 of both fluorescence curve and derivative plots 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.

y.lim.deriv

(Numeric vector with two elements) Optional: Provide the lower (l) and upper (u) bounds on the y-axis of the derivative plot 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.

n.ybreaks

(Numeric) Number of breaks on the y-axis. The breaks are generated using axisTicks(). Thus, the final number of breaks can deviate from the user input.

y.title

(Character) Optional: Provide a title for the y-axis of the growth curve plot.

x.title

(Character) Optional: Provide a title for the x-axis of both growth curve and derivative plots.

y.title.deriv

(Character) Optional: Provide a title for the y-axis of the derivative plot.

plot

(Logical) Show the generated plot in the Plots pane (TRUE) or not (FALSE). If FALSE, a ggplot object is returned.

export

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

width

(Numeric) Width of the exported image in inches.

height

(Numeric) Height 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

A plot with the nonparametric fit.

Examples

# load example dataset
input <- read_data(data.growth = system.file("lac_promoters_growth.txt", package = "QurvE"),
                   data.fl = system.file("lac_promoters_fluorescence.txt", package = "QurvE"),
                   csvsep = "\t",
                   csvsep.fl = "\t")

# Extract time and normalized fluorescence data for single sample
time <- input$time[4,]
data <- input$norm.fluorescence[4,-(1:3)] # Remove identifier columns

# Perform linear fit
TestFit <- flFitSpline(time = time,
                       fl_data = data,
                       ID = "TestFit",
                       control = fl.control(fit.opt = "s", x_type = "time"))

plot(TestFit)