Plotly or ggplot fold change plots

Usage

fcPlot(
  object,
  x1var,
  x2var,
  x1Values = NULL,
  x2Values = NULL,
  pCutoff = 0.01,
  labels = c(),
  useAdjusted = FALSE,
  plotCutoff = 1,
  graphics = "ggplot",
  fontSize = 12,
  labelFontSize = 4,
  colours = c("grey", "goldenrod1", "red", "blue"),
  verbose = FALSE,
  ...
)

Arguments

object: A glmmSeq object created by glmmSeq::glmmSeq().
x1var: The name of the first (inner) x parameter
x2var: The name of the second (outer) x parameter
x1Values: Timepoints or categories in x1var used to calculate fold change. If NULL the first two levels in x1var are used.
x2Values: Categories in x2var to be compared on x and y axis.
pCutoff: The significance cut-off for colour-coding (default = 0.01)
labels: Row names or indices to label on plot
useAdjusted: whether to use adjusted p-values (must have q-values in object). Default = FALSE
plotCutoff: Which probes to include on plot by significance cut-off (default = 1, for all markers)
graphics: Graphics system to use: "ggplot" or "plotly"
fontSize: Font size
labelFontSize: Font size for labels
colours: Vector of colours to use for significance groups
verbose: Whether to print statistics
...: Other parameters to pass to plotly or ggplot

Value

Returns a plot for fold change between x1Values in one x2Value subset on x axis and fold change in the other x2Value on the y axis.

Examples

data(PEAC_minimal_load)

disp <- apply(tpm, 1, function(x) {
(var(x, na.rm = TRUE)-mean(x, na.rm = TRUE))/(mean(x, na.rm = TRUE)**2)
})

glmmFit <- glmmSeq(~ Timepoint * EULAR_6m + (1 | PATID),
                     countdata = tpm[1:5, ],
                     metadata = metadata,
                     dispersion = disp,
                     verbose = FALSE)

fcPlot(object = glmmFit,
      x1var = "Timepoint",
      x2var = "EULAR_6m",
      x2Values = c("Good", "Non-response"),
      pCutoff = 0.05,
      useAdjusted = FALSE,
      plotCutoff = 1,
      graphics = "plotly")