maPlot: MA plots

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

MA plots

Description

MA plots

Usage

maPlot(
  object,
  x1var,
  x2var,
  x1Values = NULL,
  x2Values = NULL,
  pCutoff = 0.01,
  plotCutoff = 1,
  zeroCountCutoff = 50,
  colours = c("grey", "midnightblue", "mediumvioletred", "goldenrod"),
  labels = c(),
  fontSize = 12,
  labelFontSize = 4,
  useAdjusted = FALSE,
  graphics = "ggplot",
  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 to be 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)
plotCutoff	Which probes to include by significance cut-off (default=1 for all markers)
zeroCountCutoff	Which probes to include by minimum counts cut-off (default=50)
colours	Vector of colours to use for significance groups
labels	Row names or indices to label on plot
fontSize	Font size
labelFontSize	Font size for labels
useAdjusted	whether to use adjusted p-values (must have q-values in object)
graphics	Either "ggplot" or "plotly"
verbose	Whether to print statistics

Value

List of three plots. One plot for each x2Value and one combined figure

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)
})

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

plots <- maPlot(resultTable,
                x1var='Timepoint',
                x2var='EULAR_6m',
                x2Values=c('Good', 'Non-response'),
                graphics="plotly")

plots$combined

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