fcPlot: Plotly or ggplot fold change plots

In glmmSeq: General Linear Mixed Models for Gene-Level Differential Expression

Plotly or ggplot fold change plots

Description

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")

glmmSeq documentation built on Oct. 8, 2022, 5:05 p.m.