highlightOnPlot: Highlight features of interest on a spatial proteomics plot
In pRoloc: A unifying bioinformatics framework for spatial proteomics

Description Usage Arguments Value Author(s) Examples

Highlights a set of features of interest given as a FeaturesOfInterest instance on a PCA plot produced by codeplot2D or plot3D. If none of the features of interest are found in the MSnset's featureNames, an warning is thrown.

highlightOnPlot(object, foi, labels, args = list(), ...)

highlightOnPlot3D(object, foi, labels, args = list(), radius = 0.1 * 3,
  ...)

`object`	The main dataset described as an `MSnSet` or a `matrix` with the coordinates of the features on the PCA plot produced (and invisibly returned) by `plot2D`.
`foi`	An instance of `FeaturesOfInterest`, or, alternatively, a `character` of feautre names.
`labels`	A `character` of length 1 with a feature variable name to be used to label the features of interest. This is only valid if `object` is an `MSnSet`. Alternatively, if `TRUE`, then `featureNames(object)` (or coderownames(object), if `object` is a `matrix`) are used. Default is missing, which does not add any label.s
`args`	A named list of arguments to be passed to `plot2D` if the PCA coordinates are to be calculated. Ignored if the PCA coordinates are passed directly, i.e. `object` is a `matrix`.
`...`	Additional parameters passed to `points` or `text` (when `labels` is `TRUE`) when adding to `plot2D`, or `spheres3d` or `text3d` when adding the `plot3D`
`radius`	Radius of the spheres to be added to the visualisation produced by `plot3D`. Default is 0.3 (i.e `plot3D`'s `radius1` * 3), to emphasise the features with regard to uknown (`radius1 = 0.1`) and marker (`radius1` * 2) features.

NULL; used for its side effects.

Laurent Gatto

library("pRolocdata")
data("tan2009r1")
x <- FeaturesOfInterest(description = "A test set of features of interest",
                        fnames = featureNames(tan2009r1)[1:10],
                        object = tan2009r1)

## using FeaturesOfInterest or feature names
par(mfrow = c(2, 1))
plot2D(tan2009r1)
highlightOnPlot(tan2009r1, x)
plot2D(tan2009r1)
highlightOnPlot(tan2009r1, featureNames(tan2009r1)[1:10])

.pca <- plot2D(tan2009r1)
head(.pca)
highlightOnPlot(.pca, x, col = "red")
highlightOnPlot(tan2009r1, x, col = "red", cex = 1.5)
highlightOnPlot(tan2009r1, x, labels = TRUE)

.pca <- plot2D(tan2009r1, dims = c(1, 3))
highlightOnPlot(.pca, x, pch = "+", dims = c(1, 3))
highlightOnPlot(tan2009r1, x, args = list(dims = c(1, 3)))

.pca2 <- plot2D(tan2009r1, mirrorX = TRUE, dims = c(1, 3))
## previous pca matrix, need to mirror X axis
highlightOnPlot(.pca, x, pch = "+", args = list(mirrorX = TRUE))
## new pca matrix, with X mirrors (and 1st and 3rd PCs)
highlightOnPlot(.pca2, x, col = "red")

plot2D(tan2009r1)
highlightOnPlot(tan2009r1, x)
highlightOnPlot(tan2009r1, x, labels = TRUE, pos = 3)
highlightOnPlot(tan2009r1, x, labels = "Flybase.Symbol", pos = 1)

## in 3 dimensions
if (interactive()) {
  plot3D(tan2009r1, radius1 = 0.05)
  highlightOnPlot3D(tan2009r1, x, labels = TRUE)
  highlightOnPlot3D(tan2009r1, x)
}