I really love ggjoy and believe it can be a good tool to visualize gene set enrichment (GSEA) result. DOSE/clusterProfiler support several visualization methods.
geofacet, that supports arranging facet panels that mimics geographic topoloty.
After playing with it, I realized that it is not only for visualizing
geo-related data, but also can be fun for presenting data to mimics pixel art.
library(ggtree) tree_text <- "(((((cow, (whale, dolphin)), (pig2, boar)), camel), fish), seedling);" x <- read.tree(text=tree_text) ggtree(x, linetype="dashed", color='firebrick') + xlim(NA, 7) + ylim(NA, 8.5) + geom_tiplab(aes(color=label), parse='emoji', size=14, vjust=0.25) + labs(title="phylomoji", caption="powered by ggtree + emojifont")
ggtreeto 2 packages,
ggtreeis mainly focus on visualization and annotation, while
treeiofocus on parsing and exporting tree files. Here is a welcome message from
treeiothat you can convert
ggtreeoutput to tree object which can be exported as newick or nexus file if you want.
ggplot2, output of
ggtree is actually a
ggplot object. The
ggtree object can be rendered as graph by
as.treedata to convert
ggtree object to
For GSEA analysis, we are familar with the above figure which shows the running enrichment score. But for most of the software, it lack of visualization method to summarize the whole enrichment result.
Dear ggtree team,
how can I apply a geom_xxx to only one facet panel? For example if i want to get
geom_text()in the dot panel? I cant see the
facet_grid(. ~ var)function call, so I don’t know which subsetting to use. I have already read http://stackoverflow.com/questions/29873155/geom-text-and-facets-not-working
tr <- rtree(30) d1 <- data.frame(id=tr$tip.label, val=rnorm(30, sd=3)) p <- ggtree(tr) p2 <- facet_plot(p, panel="dot", data=d1, geom=geom_point, aes(x=val), color='firebrick') d2 <- data.frame(id=tr$tip.label, value = abs(rnorm(30, mean=100, sd=50))) p3 <- facet_plot(p2, panel='bar', data=d2, geom=geom_segment, aes(x=0, xend=value, y=y, yend=y), size=3, color='steelblue') + theme_tree2()
If this can be done, we can create even more comprehensive tree plots.
Here are the outputs produced by
aes(color=VAR)syntax. For user’s own data, it is also easy as
%<+%operator to attach user data.
Plotting pies on ggplot/ggmap is not an easy task, as ggplot2 doesn’t provide native pie geom. The pie we produced in ggplot2 is actually a barplot transform to polar coordination. This make it difficult if we want to produce a map like the above screenshot, which was posted by Tyler Rinker, the author of R package pacman.