Plotting splines

# S4 method for Moanin,matrix
plot_splines_data(
  object,
  data,
  colors = NULL,
  smooth = FALSE,
  legend = TRUE,
  legendArgs = NULL,
  subset_conditions = NULL,
  subset_data = NULL,
  simpleY = TRUE,
  centroid = NULL,
  scale_centroid = c("toData", "toCentroid", "none"),
  mar = c(2.5, 2.5, 3, 1),
  mfrow = NULL,
  addToPlot = NULL,
  ylab = "",
  xlab = "Time",
  ...
)

# S4 method for Moanin,numeric
plot_splines_data(object, data, ...)

# S4 method for Moanin,data.frame
plot_splines_data(object, data, ...)

# S4 method for Moanin,DataFrame
plot_splines_data(object, data, ...)

# S4 method for Moanin,missing
plot_splines_data(object, data, ...)

Arguments

object	An object of class `Moanin`, an object containing all related information for time course data and the splines model that will be used (if applicable). See `create_moanin_model` for more details.
data	matrix containing the data to be plotted, where each row of the data provided will be plotted as a separate plot. If missing, will rely on data in `assay(object)`
colors	vector, optional, default NULL. Vector of colors
smooth	boolean, optional, default: FALSE. Whether to smooth the centroids or not.
legend	boolean whether to include a legend (default:TRUE)
legendArgs	list of arguments to be passed to legend command (if `legend=TRUE`)
subset_conditions	list if provided, only plots the subset of conditions provided. Else, plots all conditions
subset_data	list if provided, only plots the subset of data (ie, the rows) provided. Can be any valid vector for subsetting a matrix. See details.
simpleY	boolean, if true, will plot all genes on same y-axis and minimize the annotation of the y axis to only label the axis in the exterior plots (the x-axis is always assumed to be the same across all plots and will always be simplified)
centroid	numeric vector (or matrix of 1 row) with data to use to fit the splines. If `NULL`, the splines plotted will be from the data.
scale_centroid	determines whether the centroid data given in `centroid` should be rescaled to match that of the data (`"toData"`), or the data scaled to match that of centroid (`"toCentroid"`), or simply plotted as is (`"none"`).
mar	vector of margins to set the space around each plot (see `par`)
mfrow	a vector of integers of length 2 defining the grid of plots to be created (see `par`). If missing, the function will set a value.
addToPlot	A function that will be called after the plotting, allowing the user to add more to the plot.
ylab	label for the y-axis
xlab	label for the x-axis
...	arguments to be passed to the individual plot commands (Will be sent to all plot commands)

Value

This function creates a plot and does not return anything to the user.

Details

If data is NULL, the data plotted will be from assay(object), after log-transformation if log_transform(object)=TRUE.

If centroid is missing, then splines will be estimated (per group) for the the data in data -- separately for each row of data. If centroid is provided, this data will be used to plot a spline function, and this same spline will be plotted for each row of data. This is useful, for example, in plotting cluster centroids over a series of genes.

If the user set log_transform=TRUE in the creation of the Moanin object, the data will be log transformed before plotting and calculating the spline fits.

Examples

# First, load some data and create a moanin model
data(exampleData)
moanin <- create_moanin_model(data=testData,meta=testMeta,
   degrees_of_freedom=6)

# The moanin model contains all the information for plotting purposes. The
# plot_splines_data will automatically fit the splines from the
# information contained in the moanin model
genes <- c("NM_001042489", "NM_008725")
plot_splines_data(moanin, subset_data=genes,
mfrow=c(2, 2))
# By default, same axis for all genes. Can change with 'simpleY=FALSE'
plot_splines_data(moanin, subset_data=genes,
   smooth=TRUE, mfrow=c(2,2), simpleY=FALSE)

# The splines can also be smoothed
plot_splines_data(moanin, subset_data=genes,
   smooth=TRUE, mfrow=c(2, 2))
# You can provide different data (on same subjects),
# instead of data in moanin object
# (in which case moanin just provides grouping information)
plot_splines_data(moanin, data=1/assay(moanin), subset_data=genes,
   smooth=TRUE, mfrow=c(2, 2))

# You can also provide data to use for fitting splines to argument  
# "centroid". This is helpful for overlaying centroids or predicted data
# Here we do a silly example, just to demonstrate syntax, 
# where we use the data from the first gene as our centroid to fit a
# spline estimate, but plot data from genes 3-4
plot_splines_data(moanin, centroid=assay(moanin[1,]), subset_data=3:4,
   smooth=TRUE, mfrow=c(2,2))