Compare feature expression correlation across two data sets.

plotCountsCorrelationHeatmap(x, y, ...)

# S4 method for matrix,matrix
plotCountsCorrelationHeatmap(x, y, i = NULL,
j = NULL, method = "pearson", ...)

## Arguments

x Object. Object. indices specifying elements to extract or replace. Indices are numeric or character vectors or empty (missing) or NULL. Numeric values are coerced to integer as by as.integer (and hence truncated towards zero). Character vectors will be matched to the names of the object (or for matrices/arrays, the dimnames): see ‘Character indices’ below for further details. For [-indexing only: i, j, ... can be logical vectors, indicating elements/slices to select. Such vectors are recycled if necessary to match the corresponding extent. i, j, ... can also be negative integers, indicating elements/slices to leave out of the selection. When indexing arrays by [ a single argument i can be a matrix with as many columns as there are dimensions of x; the result is then a vector with elements corresponding to the sets of indices in each row of i. An index value of NULL is treated as if it were integer(0). indices specifying elements to extract or replace. Indices are numeric or character vectors or empty (missing) or NULL. Numeric values are coerced to integer as by as.integer (and hence truncated towards zero). Character vectors will be matched to the names of the object (or for matrices/arrays, the dimnames): see ‘Character indices’ below for further details. For [-indexing only: i, j, ... can be logical vectors, indicating elements/slices to select. Such vectors are recycled if necessary to match the corresponding extent. i, j, ... can also be negative integers, indicating elements/slices to leave out of the selection. When indexing arrays by [ a single argument i can be a matrix with as many columns as there are dimensions of x; the result is then a vector with elements corresponding to the sets of indices in each row of i. An index value of NULL is treated as if it were integer(0). a character string indicating which correlation coefficient (or covariance) is to be computed. One of "pearson" (default), "kendall", or "spearman": can be abbreviated. Passthrough arguments to plotHeatmap().

## Value

Graphical output.

## Note

Updated 2019-07-29.

## Examples

data(RangedSummarizedExperiment, package = "acidtest")

## matrix ====
x <- SummarizedExperiment::assay(RangedSummarizedExperiment)
y <- x + 1L
plotCountsCorrelationHeatmap(x, y)