MA plots

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)
#> 
#> n = 123 samples, 82 individuals
#> Time difference of 0.2978292 secs

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

plots$combined