Plot Correlation Matrix

This function takes in a matrix with the predicted proportions for each spot and returns a correlation matrix between cell types.

Usage

# S4 method for matrix
plotCorrelationMatrix(
  x,
  cor.method = c("pearson", "kendall", "spearman"),
  insig = c("blank", "pch"),
  colors = c("#6D9EC1", "white", "#E46726"),
  hc.order = TRUE,
  p.mat = TRUE,
  ...
)

Arguments

x

numeric matrix with rows = samples and columns = cell types Must have at least two rows and two columns.

cor.method

Method to use for correlation: c("pearson", "kendall", "spearman"). By default pearson.

insig

character, specialized insignificant correlation coefficients, "pch", "blank" (default). If "blank", wipe away the corresponding glyphs; if "pch", add characters (see pch for details) on corresponding glyphs.

colors

character vector with three colors indicating the lower, mid, and high color. By default c("#6D9EC1", "white", "#E46726").

hc.order

logical value. If TRUE, correlation matrix will be hc.ordered using hclust function.

p.mat

logical value. If TRUE (default), correlation significance will be used. If FALSE arguments sig.level, insig, pch, pch.col, pch.cex are invalid.

...

additional graphical parameters passed to ggcorrplot.

Value

ggplot object

Author

Marc Elosua Bayes & Helena L Crowell

Examples

set.seed(321)
x <- replicate(m <- 25, runif(10, 0, 1))
rownames(x) <- paste0("spot", seq_len(nrow(x)))
colnames(x) <- paste0("type", seq_len(ncol(x)))

# The most basic example
plotCorrelationMatrix(x = x)


# Showing the non-significant correlatinos
plotCorrelationMatrix(x = x, insig = "pch")


# A more elaborated
plotCorrelationMatrix(
    x = x,
    hc.order = FALSE,
    type = "lower",
    outline.col = "lightgrey",
    method = "circle",
    colors = c("#64ccc9", "#b860bd", "#e3345d"))
#> Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> = "none")` instead.