Visualize the GO similarity matrix and the classifications

Visualize the GO similarity matrix and the classifications

ht_GO_clusters(mat, cl, dend = NULL,
    draw_word_cloud = TRUE, min_term = 5, order_by_size = FALSE,
    exclude_words = character(0), max_words = 10,
    word_cloud_grob_param = list(), fontsize_range = c(4, 16), ...)

Arguments

mat	A GO similarity matrix.
cl	Cluster labels inferred from the similarity matrix, e.g. from cluster_GO or binary_cut.
dend	Used internally.
draw_word_cloud	Whether to draw the word clouds.
min_term	Minimal number of GO terms in a cluster. All the clusters with size less than min_term are all merged into one single cluster in the heatmap.
order_by_size	Whether to reorder GO clusters by their sizes. The cluster that is merged from small clusters (size < 5) is always put to the bottom of the heatmap.
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 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.
...	Other arguments passed to draw,HeatmapList-method.

Examples

mat = readRDS(system.file("extdata", "similarity_mat.rds", package = "simplifyGO"))
cl = binary_cut(mat)
ht_GO_clusters(mat, cl, word_cloud_grob_param = list(max_width = 80))