plotFRC: plotFRC

In sysbiosig/SCRC: Fractional response analysis

Description

This functions return ggplot2 figure that visualise fractional response curve (FRC) that quantifies fractions of cells that exhibit different responses to a change in dose, or any other experimental condition.

Usage

plotFRC(
  model,
  title_ = "Fractional Response Curve",
  xlab_ = "Dose",
  ylab_ = "Cumulative fraction of cells",
  fill.guide_ = "legend",
  ylimits_ = TRUE,
  alpha_ = 0.5,
  getScaleY = getScaleY.SCRC,
  theme.signal = NULL,
  plot.heterogeneity = TRUE,
  ...
)

Arguments

model	FRAModel object return by FRA function
title_	character, specify title of plot, default "Fractional Response Curve"
xlab_	character, label of x axes, default "Dose"
ylab_	character, label of y axes and legend title, default "Cumulative fraction of cells"
fill.guide_	logical, specify if legend should be displayed
ylimits_	TRUE FALSE or vector of minimum and maximum of y axes
theme.signal	optional, object returned by GetRescaledSignalTheme
plot.heterogeneity,	logical, specify if heterogeneity should be added to FRC plot, default TRUE
...	Arguments passed on to rescaleSignalsValues rescale.fun parameter, that defines a function used for rescaling signals in plots. There are three built-in functions, that can be chosen: (1) 'factor' - signals treated as factors (default) with levels defined in list rescale.fun.args, (2) 'numeric', (3) logarithmic - with base defined in rescale.fun.args - default: e = exp(1). Function must be defined as a lambda construct function(x, ...){...}. rescale.fun.args list of the arguments to defaults rescale.fun

sysbiosig/SCRC documentation built on July 9, 2021, 9:22 p.m.