Draw a heatmap from a single SummarizedExperiment assay

Source: R/plotAssayHeatmap.R

Use ggplot2 to create a heatmap from a SummarizedExperiment object

plotAssayHeatmap(x, ...)

# S4 method for class 'SummarizedExperiment'
plotAssayHeatmap(
  x,
  assay = "counts",
  by_x = "colnames",
  facet_x = NULL,
  ysideline = FALSE,
  yside_col = NULL,
  trans = NULL,
  n_max = 100,
  ...
)

Arguments

x

a SummarizedExperiment object

...

Not used

assay

the assay to take values from

by_x

the parameter to use for the x-axis. Will default to column names but should be one value per sample, such as an additional column containing shortened sample labels.

facet_x

column from colData(x) which will be used to group samples along the x-axis

ysideline

logical(1) Draw a line across the side of the y-axis summarising values for each range

yside_col

column from colData(x) to group and colour the lines drawn on the side of the y-axis. If grouping by treatment or replicate, the mean values will be shown

trans

character(1). Any transformative function to be applied to the data before calculating the density, e.g. trans = "log2"

n_max

Maximum number of ranges to draw

Value

A ggplot2 object. Scales and labels can be added using conventional ggplot2 syntax.

Details

Draw a heatmap containing selected values from an assay within a SummarizedExperiment object. Columns within the colData element of the object can be used to facet along the x-axis (e.g. treatment groups). The maximum number of points is set to be 100, although this can be changed easily should the plot require more ranges to be drawn.

The averages across any grouping of samples can be drawn as a line plot on the side of the y-axis by setting ysideline = TRUE, with groups as specified in yside_col. This feature is added for the specific context of neighbouring or overlapping ranges, and as such may be less informative in any other scenario

The returned object is a ggplot2 object so scales can easily be added after heatmap creation using scale_fill_\* for the main heatmap, and scale_colour_\* for any groupings along the y-axis

Examples

nrows <- 10; ncols <- 4
counts <- matrix(runif(nrows * ncols, 1, 1e4), nrows)
colnames(counts) <- paste0("Sample_", seq_len(ncols))
df <- DataFrame(treat = c("A", "A", "B", "B"))
se <- SummarizedExperiment(
  assays = SimpleList(counts = counts),
  colData = df
)
rowRanges(se) <- GRanges(paste0("chr1:", seq_len(nrows)))
plotAssayHeatmap(se, facet_x = "treat")