| modelPlot | R Documentation | 
Plot to show differences between groups over time using base graphics.
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, ... )
object | 
 A glmmSeq/lmmSeq object created by
  | 
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   | 
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   | 
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
  | 
Returns a paired plot for matched samples
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')
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