Generates a chord diagram or alluvial plot for visualising changes in localisation between two conditions/datasets

Produces a chord diagram (circos plot) or an alluvial plot (also known as a Sankey diagram) to show changes in location between two conditions or datasets.

plotTranslocations(
  params,
  type = "alluvial",
  all = FALSE,
  fcol,
  col,
  labels = TRUE,
  labels.par = "adj",
  cex = 1,
  spacer = 4,
  ...
)

Arguments

params: An instance of class bandleParams or an instance of class MSnSetList of length 2.
type: A character specifying the type of visualisation to plot. One of "alluvial" (default) or "chord".
all: A logical specifying whether to count all proteins or only show those that have changed in location between conditions. Default is FALSE.
fcol: If params is a list of MSnSets. Then fcol must be defined. This is a character vector of length 2 to set different labels for each dataset. If only one label is specified, and the character is of length 1 then this single label will be used to identify the annotation column in both datasets.
col: A list of colours to define the classes in the data. If not defined then the default pRoloc colours in getStockCol() are used.
labels: Logical indicating whether to display class/organelle labels for the chord segments or alluvial stratum. Default is TRUE.
labels.par: If type is "alluvial". Label style can be specified as one of "adj", "repel". Default is "adj".
cex: Text size. Default is 1.
spacer: A numeric. Default is 4. Controls the white space around the circos plotting region.
...: Additional arguments passed to the chordDiagram function.

Value

Returns a directional circos/chord diagram showing the translocation of proteins between conditions. If type = "alluvial" ouput is a ggplot object.

Examples

## Generate some example data
library("pRolocdata")
data("tan2009r1")
set.seed(1)
tansim <- sim_dynamic(object = tan2009r1, 
                      numRep = 4L,
                      numDyn = 100L)
data <- tansim$lopitrep
control <- data[1:2]
treatment <- data[3:4]

## fit GP params
gpParams <- lapply(tansim$lopitrep, function(x) 
fitGPmaternPC(x, hyppar = matrix(c(0.5, 1, 100), nrow = 1)))

## run bandle
res <- bandle(objectCond1 = control,
              objectCond2 = treatment, 
              gpParams = gpParams,
              fcol = "markers",  
              numIter = 5L, 
              burnin = 1L, 
              thin = 2L,
              numChains = 1, 
              BPPARAM = SerialParam(RNGseed = 1),
              seed = 1)
#> 
  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |==============                                                        |  20%
  |                                                                            
  |============================                                          |  40%
  |                                                                            
  |==========================================                            |  60%
               
## Process the results
bandleres <- bandleProcess(res)

## plot the results
plotTranslocations(bandleres)
#> Warning: `spread_()` was deprecated in tidyr 1.2.0.
#> Please use `spread()` instead.
#> This warning is displayed once every 8 hours.
#> Call `lifecycle::last_lifecycle_warnings()` to see where this warning was generated.
#> Warning: The `.dots` argument of `group_by()` is deprecated as of dplyr 1.0.0.
#> This warning is displayed once every 8 hours.
#> Call `lifecycle::last_lifecycle_warnings()` to see where this warning was generated.

plotTranslocations(bandleres, type = "chord")