glmmSeq (version 0.0.1)

maPlot: MA plots

Description

MA plots

Usage

maPlot(
  glmmResult,
  x1Label,
  x2Label,
  x1Values = NULL,
  x2Values = NULL,
  pCutoff = 0.01,
  plotCutoff = 1,
  zeroCountCutoff = 50,
  colours = c("grey", "midnightblue", "mediumvioletred", "goldenrod"),
  labels = c(),
  fontSize = 12,
  labelFontSize = 5,
  useAdjusted = FALSE,
  graphics = "ggplot",
  verbose = FALSE
)

Arguments

glmmResult

A glmmSeq object created by glmmSeq::glmmSeq().

x1Label

The name of the first (inner) x parameter

x2Label

The name of the second (outer) x parameter

x1Values

Subpopulations in x1Label to be used to calculate fold change. If NULL the first two levels in x1Label are used.

x2Values

Subpopulations in x2Label 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 pvalues (must have q_ columns in glmmResult)

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

# NOT RUN {
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),
                       id = "PATID",
                       countdata = tpm[1:5, ],
                       metadata = metadata,
                       dispersion = disp)

plots <- maPlot(resultTable,
                x1Label='Timepoint',
                x2Label='EULAR_6m',
                x2Values=c('Good responder', 'Non responder'),
                graphics="plotly")

plots$combined
# }