plot_heatmap: Plot a heatmap.

In MonashBioinformaticsPlatform/varistran: Variance Stabilizing Transformations appropriate for RNA-Seq expression data

Description

Produces a heatmap as a grid grob.

Usage

plot_heatmap(
  y,
  cluster_samples = FALSE,
  cluster_features = TRUE,
  sample_labels = NULL,
  feature_labels = NULL,
  baseline = NULL,
  baseline_label = "row\nmean",
  scale_label = "difference from\nrow mean",
  n = Inf
)

Arguments

y	A matrix of expression levels, such as a transformed counts matrix as produced by varistran::vst.
cluster_samples	Should samples (columns) be clustered?
cluster_features	Should features (rows) be clustered?
sample_labels	Names for each sample. If not given and y has column names, these will be used instead.
feature_labels	Names for each feature. If not given and y has row names, these will be used instead.
baseline	Baseline level for each row, to be subtracted when drawing the heatmap colors. If omitted, the row mean will be used. Specify baseline=0 to not subtract anything and not show a baseline bar graph.
baseline_label	Text description of what the baseline is.
scale_label	Text description of what the heatmap colors represent (after baseline is subtracted).
n	Show only this many rows. Rows are selected in order of greatest span of expression level.

Details

This heatmap differs from other heatmaps in R in the method of clustering used:

1. The distances used are cosine distances (i.e. the magnitude of log fold changes is not important, only the pattern).

2. hclust() is used to produce a clustering, as normal.

3. Branches in the hierarchical clustering are flipped to minimize sharp changes between neighbours, using the seriation package's OLO (Optimal Leaf Ordering) method.

Value

A grid grob. print()-ing this value will cause it to be displayed.

Additionally $info$row_order will contain row ordering and $info$col_order will contain column ordering.

Author(s)

Paul Harrison.

Examples

# Generate some random data.
counts <- matrix(rnbinom(1000, size=1/0.01, mu=100), ncol=10)

y <- varistran::vst(counts, cpm=TRUE)
print( varistran::plot_heatmap(y, n=20) )

MonashBioinformaticsPlatform/varistran documentation built on March 21, 2020, 3:20 p.m.