plot_splines_data {moanin} | R Documentation |
Plotting splines
## 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, ...)
object |
An object of class |
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 |
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
|
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 |
scale_centroid |
determines whether the centroid data given in
|
mar |
vector of margins to set the space around each plot (see
|
mfrow |
a vector of integers of length 2 defining the grid of plots to be
created (see |
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) |
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.
This function creates a plot and does not return anything to the user.
# 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))