simplifyGO {simplifyEnrichment} | R Documentation |
Simplify Gene Ontology (GO) enrichment results
simplifyGO(mat, method = "binary_cut", control = list(), plot = TRUE, term = NULL, verbose = TRUE, column_title = qq("@{nrow(mat)} GO terms clustered by '@{method}'"), ht_list = NULL, ...)
mat |
A GO similarity matrix. |
method |
Method for clustering the matrix. See |
control |
A list of parameters for controlling the clustering method, passed to |
plot |
Whether to make the heatmap. |
term |
The full name or the description of the corresponding GO IDs. The values are automatically extracted if it is not provided. |
column_title |
Column title for the heatmap. |
verbose |
Whether to print messages. |
ht_list |
A list of additional heatmaps added to the left of the similarity heatmap. |
... |
Arguments passed to |
This is basically a wrapper function that it first runs cluster_terms
to cluster
GO terms and then runs ht_clusters
to visualize the clustering.
The arguments in simplifyGO
passed to ht_clusters
are:
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 < min_term
) 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 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.
bg_gp
Graphic parameters for controlling the background of word cloud annotations.
A data frame with three columns: GO IDs, GO term names and cluster labels.
simplifyGOFromMultipleLists
which performs simplifyGO analysis with multiple lists of GO IDs.
set.seed(123) go_id = random_GO(500) mat = GO_similarity(go_id) df = simplifyGO(mat, word_cloud_grob_param = list(max_width = 80)) head(df)