This can be quite easy to implement in ggtree, I can write a
geom layer to layout the alignment. As ggbio already provides many
geom for genomic data and I don’t want to re-invent the wheel, I decided to try
ggtree+ggbio. This is also the beauty of
R that packages complete each others.
I am using dotplot() to visualize results from enrichGO(), enrichDO(), enricher() and compareCluster() in clusterProfiler R package. When specifying showCategory, I get the right number of categories except with the results of compareCluser().
In my case, I use compareCluster() on a list of 3 elements:
str(ClusterList) List of 3 $ All : chr [1:1450] "89886" "29923" "100132891" "101410536" ... $ g1 : chr [1:858] "89886" "29923" "100132891" "101410536" ... $ g2: chr [1:592] "5325" "170691" "29953" "283392" ... CompareGO_BP=compareCluster(ClusterList, fun="enrichGO", pvalueCutoff=0.01, pAdjustMethod="BH", OrgDb=org.Hs.eg.db,ont="BP",readable=T) dotplot(CompareGO_BP, showCategory=10, title="GO - Biological Process")
I ask for 10 categories, but I get 15 categories in All, 8 categories in g1 and 12 categories in g2. None of the categories, neither the sum of the categories are 10…
Is the option showCategory working in the case of comparison? Am I missing something here?
And which categories precisely will it plot? the most significant whatever my 3 cases or the most significant of each case?
The question was posted in Bioconductor support site. It seems quite confusing and I think I need to write a post to clarify it.
I try to plot long tip labels in ggtree and usually adjust them using xlim(), however when creating a facet_plot xlim affects all plots and minimizes them.
Is it possible to work around this and only affect the tree and it’s tip labels leaving the other plots in facet_plot unaffected?
This is indeed a desire feature, as
ggplot2 can’t automatically adjust
xlim for text since the units are in two different spaces (data and pixel).
gheatmapfor visualizing heatmap and
msaplotfor visualizing multiple sequence alignment with phylogenetic tree.
We may have different data types and want to visualize and align them with the tree. For example,
dotplot of SNP site (e.g. using
barplot of trait values (e.g. using
geom_barh(stat='identity')) et al.
To make it easy to associate different types of data with phylogenetic tree, I implemented the
facet_plot function which accepts a
geom function to draw the input
data.frame and display it in an additional
Here, as examples, I used
ggtree to draw capital character
C, which are first letter of my name :-).
To draw a tree in such shape, we need
fan layout (
circular layout with open angle) and then rotating the tree to let the open space on the correct position. Here are the source codes to produce the
C shapes of tree. I am thinking about using the
G shaped tree as
ggtree logo. Have fun with
obkData to store case-base outbreak data. It also provides a function,
plotggphy, to visualize such data on the phylogenetic tree.
library(OutbreakTools) data(FluH1N1pdm2009) attach(FluH1N1pdm2009) x <- new("obkData", individuals = individuals, dna = FluH1N1pdm2009$dna, dna.individualID = samples$individualID, dna.date = samples$date, trees = FluH1N1pdm2009$trees) plotggphy(x, ladderize = TRUE, branch.unit = "year", tip.color = "location", tip.size = 3, tip.alpha = 0.75)
phyloseq class defined in the phyloseq package was designed for microbiome data.
phyloseq package implemented
plot_tree function using
ggplot2. Although the function was implemented by
ggplot2 and we can use
scale_color_manual etc for customization, the most valuable part of
ggplot2, adding layer, is missing.
plot_tree only provides limited parameters to control the output graph and it is hard to add layer unless user has expertise in both
MeSH.dbcontains 16 of them. That is: