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)))`.
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
if (FALSE) { # \dontrun{
# 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)
} # }