plot_splines_data: Plotting splines

In NelleV/moanin: An R Package for Time Course RNASeq Data Analysis

Description

Plotting splines

Usage

## S4 method for signature '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 = "",
  xaxis = TRUE,
  yaxis = TRUE,
  xlab = "Time",
  ...
)

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

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

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

## S4 method for signature '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
xaxis	Logical, whether to add x-axis labels to plot (if FALSE can be manually created by user with call to addToPlot)
yaxis	Logical, whether to add y-axis labels to plot (if FALSE can be manually created by user with call to addToPlot)
xlab	label for the x-axis
...	arguments to be passed to the individual plot commands (Will be sent to all plot commands)

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.

Value

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

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))

NelleV/moanin documentation built on July 28, 2021, 7:34 p.m.