emapplot | R Documentation |
Enrichment Map for enrichment result of over-representation test or gene set enrichment analysis
emapplot(x, ...)
## S4 method for signature 'enrichResult'
emapplot(x, showCategory = 30, ...)
## S4 method for signature 'gseaResult'
emapplot(x, showCategory = 30, ...)
## S4 method for signature 'compareClusterResult'
emapplot(x, showCategory = 30, ...)
emapplot_internal(
x,
layout = igraph::layout_with_kk,
showCategory = 30,
color = "p.adjust",
size_category = 1,
min_edge = 0.2,
color_edge = "grey",
size_edge = 0.5,
node_label = "category",
pie = "equal",
group = FALSE,
group_style = "ggforce",
label_group_style = "shawdowtext",
label_format = 30,
clusterFunction = stats::kmeans,
nWords = 4,
nCluster = NULL
)
x |
Enrichment result. |
... |
Additional parameters |
showCategory |
A number or a vector of terms. If it is a number, the first n terms will be displayed. If it is a vector of terms, the selected terms will be displayed. |
layout |
igraph layout |
color |
Variable that used to color enriched terms, e.g. 'pvalue', 'p.adjust' or 'qvalue'. |
size_category |
relative size of the categories |
min_edge |
The minimum similarity threshold for whether two nodes are connected, should between 0 and 1, default value is 0.2. |
color_edge |
color of the network edge |
size_edge |
relative size of edge width |
node_label |
Select which labels to be displayed, one of 'category', 'group', 'all' and 'none'. |
pie |
one of 'equal' or 'Count' to set the slice ratio of the pies |
group |
logical, if TRUE, group the category. |
group_style |
style of ellipse, one of "ggforce" an "polygon". |
label_group_style |
style of group label, one of "shadowtext" and "ggforce". |
label_format |
a numeric value sets wrap length, alternatively a custom function to format axis labels. |
clusterFunction |
function of Clustering method, such as stats::kmeans(the default), cluster::clara, cluster::fanny or cluster::pam. |
nWords |
Numeric, the number of words in the cluster tags, the default value is 4. |
nCluster |
Numeric, the number of clusters, the default value is square root of the number of nodes. |
This function visualizes gene sets as a network (i.e. enrichment map). Mutually overlapping gene sets tend to cluster together, making it easier for interpretation. When the similarity between terms meets a certain threshold (default is 0.2, adjusted by parameter 'min_edge'), there will be edges between terms. The stronger the similarity, the shorter and thicker the edges. The similarity between terms is obtained by function 'pairwise_termsim', the details of similarity calculation can be found in its documentation: pairwise_termsim.
ggplot object
Guangchuang Yu
## Not run:
library(DOSE)
data(geneList)
de <- names(geneList)[1:100]
x <- enrichDO(de)
x2 <- pairwise_termsim(x)
emapplot(x2)
# use `layout` to change the layout of map
emapplot(x2, layout = "star")
# use `showCategory` to select the displayed terms. It can be a number of a vector of terms.
emapplot(x2, showCategory = 10)
categorys <- c("pre-malignant neoplasm", "intestinal disease",
"breast ductal carcinoma")
emapplot(x2, showCategory = categorys)
# It can also graph compareClusterResult
library(clusterProfiler)
library(DOSE)
library(org.Hs.eg.db)
data(gcSample)
xx <- compareCluster(gcSample, fun="enrichGO", OrgDb="org.Hs.eg.db")
xx2 <- pairwise_termsim(xx)
emapplot(xx2)
## End(Not run)
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