heat {microbiome} | R Documentation

## Association Heatmap

### 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, text.size = 10,
      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.
`text.size` | Adjust text size
`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 microbiome-admin@googlegroups.com

### 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')

[Package microbiome version 1.2.1 Index]