heat: Association Heatmap

In microbiome: Microbiome Analytics

Description

Visualizes n x m association table as heatmap.

Usage

heat(
  df,
  Xvar = names(df)[[1]],
  Yvar = names(df)[[2]],
  fill = names(df)[[3]],
  star = NULL,
  p.adj.threshold = 1,
  association.threshold = 0,
  step = 0.2,
  colours = c("darkblue", "blue", "white", "red", "darkred"),
  limits = NULL,
  legend.text = "",
  order.rows = TRUE,
  order.cols = TRUE,
  filter.significant = TRUE,
  star.size = NULL,
  plot.values = FALSE
)

Arguments

df	Data frame. Each row corresponds to a pair of associated variables. The columns give variable names, association scores and significance estimates.
Xvar	X axis variable column name. For instance 'X'.
Yvar	Y axis variable column name. For instance 'Y'.
fill	Column to be used for heatmap coloring. For instance 'association'.
star	Column to be used for cell highlighting. For instance 'p.adj'.
p.adj.threshold	Significance threshold for the stars.
association.threshold	Include only elements that have absolute association higher than this value
step	color interval
colours	heatmap colours
limits	colour scale limits
legend.text	legend text
order.rows	Order rows to enhance visualization interpretability. If this is logical, then hclust is applied. If this is a vector then the rows are ordered using this index.
order.cols	Order columns to enhance visualization interpretability. If this is logical, then hclust is applied. If this is a vector then the rows are ordered using this index.
filter.significant	Keep only the elements with at least one significant entry
star.size	NULL Determine size of the highlight symbols
plot.values	Show values as text

Value

ggplot2 object

Author(s)

Contact: Leo Lahti [e-mail]

References

See citation('microbiome')

Examples

data(peerj32)
d1 <- peerj32$lipids[, 1:10]
d2 <- peerj32$microbes[, 1:10]
cc <- associate(d1, d2, method='pearson') 
p <- heat(cc, 'X1', 'X2', 'Correlation', star='p.adj')

microbiome documentation built on Nov. 8, 2020, 5:08 p.m.