ht_clusters: Visualize the similarity matrix and the clustering
In simplifyEnrichment: Simplify Functional Enrichment Results

Description Usage Arguments Value Examples

Visualize the similarity matrix and the clustering

ht_clusters(mat, cl, dend = NULL, col = c("white", "red"),
    draw_word_cloud = is_GO_id(rownames(mat)[1]) || !is.null(term),
    term = NULL, min_term = 5,
    order_by_size = FALSE, cluster_slices = FALSE,
    exclude_words = character(0), max_words = 10,
    word_cloud_grob_param = list(), fontsize_range = c(4, 16),
    column_title = NULL, ht_list = NULL, use_raster = TRUE, ...)

`mat`	A similarity matrix.
`cl`	Cluster labels inferred from the similarity matrix, e.g. from `cluster_terms` or `binary_cut`.
`dend`	Used internally.
`col`	A vector of colors that map from 0 to the 95^th percentile of the similarity values.
`draw_word_cloud`	Whether to draw the word clouds.
`term`	The full name or the description of the corresponding GO IDs.
`min_term`	Minimal number of functional terms in a cluster. All the clusters with size less than `min_term` are all merged into one separated cluster in the heatmap.
`order_by_size`	Whether to reorder clusters by their sizes. The cluster that is merged from small clusters (size < `min_term`) is always put to the bottom of the heatmap.
`cluster_slices`	Whether to cluster slices.
`exclude_words`	Words that are excluded in the word cloud.
`max_words`	Maximal number of words visualized in the word cloud.
`word_cloud_grob_param`	A list of graphic parameters passed to `word_cloud_grob`.
`fontsize_range`	The range of the font size. The value should be a numeric vector with length two. The minimal font size is mapped to word frequency value of 1 and the maximal font size is mapped to the maximal word frequency. The font size interlopation is linear.
`column_title`	Column title for the heatmap.
`ht_list`	A list of additional heatmaps added to the left of the similarity heatmap.
`use_raster`	Whether to write the heatmap as a raster image.
`...`	Other arguments passed to `draw,HeatmapList-method`.

A HeatmapList-class object.

mat = readRDS(system.file("extdata", "random_GO_BP_sim_mat.rds",
    package = "simplifyEnrichment"))
cl = binary_cut(mat)
ht_clusters(mat, cl, word_cloud_grob_param = list(max_width = 80))
ht_clusters(mat, cl, word_cloud_grob_param = list(max_width = 80),
    order_by_size = TRUE)