fcPlot {glmmSeq} | R Documentation |
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
|
x1var |
The name of the first (inner) x parameter |
x2var |
The name of the second (outer) x parameter |
x1Values |
Timepoints or categories in |
x2Values |
Categories in |
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
|
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")