Displays a spatial proteomics animation

Given two MSnSet instances of one MSnSetList with at least two items, this function produces an animation that shows the transition from the first data to the second.

Usage

move2Ds(object, pcol, fcol = "markers", n = 25, hl)

Arguments

object: An linkS4class{MSnSet} or a MSnSetList. In the latter case, only the two first elements of the list will be used for plotting and the others will be silently ignored.
pcol: If object is an MSnSet, a factor or the name of a phenotype variable (phenoData slot) defining how to split the single MSnSet into two or more data sets. Ignored if object is a MSnSetList.
fcol: Feature meta-data label (fData column name) defining the groups to be differentiated using different colours. Default is markers. Use NULL to suppress any colouring.
n: Number of frames, Default is 25.
hl: An optional instance of class linkS4class{FeaturesOfInterest} to track features of interest.

Value

Used for its side effect of producing a short animation.

Author

Laurent Gatto

Examples

library("pRolocdata")
data(dunkley2006)

## Create a relevant MSnSetList using the dunkley2006 data
xx <- split(dunkley2006, "replicate")
xx1 <- xx[[1]]
xx2 <- xx[[2]]
fData(xx1)$markers[374] <- "Golgi"
fData(xx2)$markers[412] <- "unknown"
xx@x[[1]] <- xx1
xx@x[[2]] <- xx2

## The features we want to track
foi <- FeaturesOfInterest(description = "test",
                          fnames = featureNames(xx[[1]])[c(374, 412)])

## (1) visualise each experiment separately
par(mfrow = c(2, 1))
plot2D(xx[[1]], main = "condition A")
highlightOnPlot(xx[[1]], foi)
plot2D(xx[[2]], mirrorY = TRUE, main = "condition B")
highlightOnPlot(xx[[2]], foi, args = list(mirrorY = TRUE))


## (2) plot both data on the same plot
par(mfrow = c(1, 1))
tmp <- plot2Ds(xx) 
highlightOnPlot(data1(tmp), foi, lwd = 2)
highlightOnPlot(data2(tmp), foi, pch = 5, lwd = 2)


## (3) create an animation
move2Ds(xx, pcol = "replicate")

























move2Ds(xx, pcol = "replicate", hl = foi)