Description Usage Arguments Details Value Examples
Functional grouping tree diagram for enrichment result of over-representation test or gene set enrichment analysis.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | treeplot(x, showCategory = 30, color = "p.adjust", label_format = 30, ...)
## S4 method for signature 'enrichResult'
treeplot(x, showCategory = 30, color = "p.adjust", label_format = 30, ...)
## S4 method for signature 'gseaResult'
treeplot(x, showCategory = 30, color = "p.adjust", label_format = 30, ...)
## S4 method for signature 'compareClusterResult'
treeplot(x, showCategory = 5, color = "p.adjust", label_format = 30, ...)
treeplot.enrichResult(
x,
showCategory = 30,
color = "p.adjust",
nWords = 4,
nCluster = 5,
cex_category = 1,
label_format = 30,
xlim = NULL,
fontsize = 4,
offset = NULL,
offset_tiplab = 0.35,
hclust_method = "ward.D",
group_color = NULL,
extend = 0.3,
hilight = TRUE,
...
)
treeplot.compareClusterResult(
x,
showCategory = 5,
color = "p.adjust",
nWords = 4,
nCluster = 5,
cex_category = 1,
split = NULL,
label_format = 30,
xlim = NULL,
fontsize = 4,
offset = NULL,
pie = "equal",
legend_n = 3,
offset_tiplab = 0.5,
hclust_method = "ward.D",
group_color = NULL,
extend = 0.3,
hilight = TRUE,
...
)
|
x |
enrichment result. |
showCategory |
number of enriched terms to display |
color |
variable that used to color enriched terms, e.g. pvalue, p.adjust or qvalue |
label_format |
a numeric value sets wrap length, alternatively a custom function to format axis labels. |
... |
additional parameters |
nWords |
The number of words in the cluster tags. |
nCluster |
The number of clusters, the default value is 5. |
cex_category |
Number indicating the amount by which plotting category. nodes should be scaled relative to the default. |
xlim |
Limits for the x axes, e.g. c(0, 40). If the picture is not displayed completely, the user can increase this value. |
fontsize |
The size of text, default is 4. |
offset |
Distance bar and tree, offset of bar and text from the clade. |
offset_tiplab |
Tiplab offset, the bigger the number, the farther the distance between the node and the branch. The default value is 0.35. |
hclust_method |
Method of hclust. This should be (an unambiguous abbreviation of) one of "ward.D", "ward.D2", "single", "complete", "average" (= UPGMA), "mcquitty" (= WPGMA), "median" (= WPGMC) or "centroid" (= UPGMC). |
group_color |
A vector of group colors, the length of the vector should be the same as nCluster. |
extend |
Numeric, extend the length of bar, default is 0.3. |
hilight |
Logical value, if TRUE(default), add ggtree::geom_hilight() layer. |
split |
Separate result by 'category' variable. |
pie |
Proportion of clusters in the pie chart, one of 'equal' (default) and 'Count'. |
legend_n |
Number of circle in legend, the default value is 3. |
This function visualizes gene sets as a tree. Gene sets with high similarity tend to cluster together, making it easier for interpretation.
ggplot object
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | ## Not run:
library(clusterProfiler)
library(org.Hs.eg.db)
library(enrichplot)
library(GOSemSim)
library(DOSE)
data(geneList)
gene <- names(geneList)[abs(geneList) > 2]
ego <- enrichGO(gene = gene,
universe = names(geneList),
OrgDb = org.Hs.eg.db,
ont = "BP",
pAdjustMethod = "BH",
pvalueCutoff = 0.01,
qvalueCutoff = 0.05,
readable = TRUE)
d <- godata('org.Hs.eg.db', ont="BP")
ego2 <- pairwise_termsim(ego, method = "Wang", semData = d)
treeplot(ego2, showCategory = 30)
# use `hilight = FALSE` to remove ggtree::geom_hilight() layer.
treeplot(ego2, showCategory = 30, hilight = FALSE)
# use `offset` parameter to adjust the distance of bar and tree.
treeplot(ego2, showCategory = 30, hilight = FALSE, offset = 8)
# use `offset_tiplab` parameter to adjust the distance of nodes and branches.
treeplot(ego2, showCategory = 30, hilight = FALSE, offset_tiplab = 0.3)
keep <- rownames(ego2@termsim)[c(1:10, 16:20)]
keep
treeplot(ego2, showCategory = keep)
treeplot(ego2, showCategory = 20,
group_color = c("#999999", "#E69F00", "#56B4E9", "#009E73", "#F0E442"))
## End(Not run)
|
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