plot_effect_heatmap: Draw a heatmap of effects between variables, such as...
In antonvsdata/amp: Smoothing Metabolomics Analyses

Description Usage Arguments Details Value See Also Examples

Draws a heatmap of e.g. correlations between variables (see perform_correlation_tests). It is possible to draw only the lower triangular of the heatmap, order rows and columns with hierarchical clustering, and add circles for p-values.

plot_effect_heatmap(data, x, y, effect, p = NULL, p_limit = 0.1,
  point_size_range = c(1, 6), log2_effect = FALSE,
  discretize_effect = FALSE, breaks = 5, clustering = TRUE,
  dist_method = "euclidean", clust_method = "ward.D2",
  lower_tri = FALSE, reverse_y = TRUE, title = NULL,
  subtitle = NULL, fill_scale = NULL)

`data`	a data frame with x and y variables and the effect (used to fill the tiles)
`x, y`	the column names of data with the x and y variables
`effect`	the column name of the effect, e.g. correlation
`p`	optional, the column name with p-values. If provided, points that scale by p-value are drawn on top of the heatmap tiles
`p_limit`	numeric, only p-values below the limit are plotted as points
`point_size_range`	a numeric vector of length 2. The upper and lower limits for the point sizes. This needs to be adjusted to make the point size look good when compared to the tiles
`log2_effect`	logical, whether the effect should be plotted on a logarithmic scale (in case of fold change etc.)
`discretize_effect`	logical, whether the effect range should be divided into discrete levels instead of using a continuous scale. Can sometimes make patterns more visible, but the hard limits can blur the big picture as well.
`breaks`	if `discretize_effect = TRUE`, either the number of breaks or the points where to cut for the levels, see `cut`
`clustering`	logical, whether the order of rows and columns should be ordered by hierarchical clustering?
`dist_method`	distance method used in clustering, see `dist`
`clust_method`	clustering method used in clustering, see `hclust`
`lower_tri`	logical, should only the lower triangular be plotted?
`reverse_y`	logical, if `clustering = FALSE, lower_tri = FALSE`, should the order of the y-axis be reversed so that the diagonal is from top left to bottom right?
`title, subtitle`	the title and subtitle of the plot
`fill_scale`	fill scale for the heatmap as returned by a ggplot function

All missing effects between variables are replaced by 0 before clustering, since hclust can't deal with missing values.

a ggplot object

cut for discretizing the effect, dist for distance calculation for clustering, hclust for hierarchical clustering.

# Compute correlations between variables
correlations <- perform_correlation_tests(example_set, x = featureNames(example_set), duplicates = TRUE)

# Minimal example
plot_effect_heatmap(correlations, x = "X", y = "Y", effect = "Correlation_coefficient")

# Lower triangular with discrete effect and p-value dots
plot_effect_heatmap(correlations, x = "X", y = "Y", effect = "Correlation_coefficient", p = "Correlation_P",
               point_size_range = c(2,8),
               discretize_effect = TRUE, breaks = 7, lower_tri = TRUE)