modelPlot: Mixed model effects plot

Description

Plot to show differences between groups over time using base graphics.

Usage

modelPlot(
  object,
  geneName = NULL,
  x1var = NULL,
  x2var = NULL,
  x2shift = NULL,
  xlab = NA,
  ylab = geneName,
  plab = NULL,
  title = geneName,
  logTransform = is(object, "GlmmSeq"),
  shapes = 21,
  colours = "grey60",
  lineColours = "grey60",
  markerSize = 0.5,
  fontSize = NULL,
  alpha = 0.7,
  addModel = TRUE,
  addPoints = TRUE,
  modelSize = 2,
  modelColours = "royalblue",
  modelLineSize = 1,
  modelLineColours = modelColours,
  errorBarLwd = 2.5,
  errorBarLength = 0.05,
  ...
)

Value

Returns a paired plot for matched samples

Arguments

object: A glmmSeq/lmmSeq object created by glmmSeq::glmmSeq() or glmmSeq::lmmSeq()
geneName: The gene/row name to be plotted
x1var: The name of the first (inner) x parameter, typically 'time'. This is anticipated to have different values when matched by ID.
x2var: The name of an optional second (outer) x parameter, which should be a factor.
x2shift: Amount to shift along x axis for each level of x2var. By default the function will arrange each level of x2var side by side. Lower values of x2shift or x2shift = 0 can be used to overlap plots similar to 'dodge' or stagger them.
xlab: Title for the x axis
ylab: Title for the y axis
plab: Optional character vector of labels for p-values. These must align with column names in object@stats$pvals.
title: Plot title. If NULL gene name is used
logTransform: Whether to perform a log10 transform on the y axis
shapes: The marker shapes (default=19)
colours: The marker colours (default='red') as vector or named vector
lineColours: The line colours (default='grey60') as vector or named vector
markerSize: Size of markers (default=2)
fontSize: Plot font size
alpha: Line and marker opacity (default=0.7)
addModel: Whether to add the fit model with markers (default=TRUE)
addPoints: Whether to add underlying data points (default=TRUE)
modelSize: Size of model points (default=2)
modelColours: Colour of model fit markers (default="black") as vector or named vector
modelLineSize: Size of model points (default=1) as vector or named vector
modelLineColours: Colour of model fit lines.
errorBarLwd: Line width of error bars
errorBarLength: Head width of error bars
...: Other parameters to pass to graphics::plot()

Examples

Run this code

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)
})

MS4A1glmm <- glmmSeq(~ Timepoint * EULAR_6m + (1 | PATID),
                     countdata = tpm[1:2, ],
                     metadata = metadata,
                     dispersion = disp)

modelPlot(object=MS4A1glmm,
          geneName = 'MS4A1',
          x1var = 'Timepoint',
          x2var='EULAR_6m')

Run the code above in your browser using DataLab