Pairwise cross-plot of spatial associations

Builds a pairwise scatterplot of marker-marker associations for a single image using the output of getPairwise().

Usage

imageCrossPlot(
  result,
  image = NULL,
  colourGradient = c("#4575B4", "white", "#D73027"),
  marksToPlot = NULL,
  limits = NULL
)

Arguments

result: A matrix or data frame produced by getPairwise() where rownames are image IDs and colnames are concatenated marker pairs in the form "from__to". Must contain at least one row with name matching image.
image: Character scalar. Which image (row in result) to plot. If NULL, defaults to the first rowname of result.
colourGradient: Character vector of length 3 giving the low, mid, and high colours for a diverging palette used by scale_colour_gradient2(). Default is c("#4575B4", "white", "#D73027").
marksToPlot: Optional character vector of marker names. If supplied, the plot is restricted to rows and columns where both from and to are in this set.
limits: Numeric length-2 vector giving the lower and upper caps applied to association values for colour mapping. Use NULL to avoid clamping. Point sizes are clamped to c(0, max(abs(limits))).

Value

A ggplot2 object.

Details

The function expects colnames(result) to contain "__" separating marker names; otherwise an error is thrown. Values are transformed into two aesthetics:

value: the (possibly clamped) signed association used for colour.
size: the (possibly clamped) absolute association used for point size.

The colourbar shows three ticks at lower, 0, and upper with labels "<lower", "0", and ">upper".

Examples

# Minimal example (toy data)
set.seed(1)
mks <- c("A","B","C")
pairs <- as.vector(outer(mks, mks, paste, sep="__"))
res <- matrix(rnorm(length(pairs)*2), nrow = 2,
              dimnames = list(c("img1","img2"), pairs))

p <- imageCrossPlot(res, image = "img1",
                       colourGradient = c("#4575B4","white","#D73027"),
                       marksToPlot = c("A","B","C"),
                       limits = c(-3, 3))
print(p)