更新R较为无痛的方法已经在hello yosemite一文中提及。今天Bioconductor发布3.4版本,又是更新R包的时候了。
之前为了吐槽很多人问问题都是在使用早已不维护的老版本,写了rvcheck来帮忙检查版本。既然能够帮我们检查版本,自然能够帮忙升级。
使用rvcheck::update_all()
可以自动更新CRAN, Bioconductor和Github上的R包。其实可以放到系统任务里,每月自动更新一次,然后就可以完全不用管升级的事情。
更新R较为无痛的方法已经在hello yosemite一文中提及。今天Bioconductor发布3.4版本,又是更新R包的时候了。
之前为了吐槽很多人问问题都是在使用早已不维护的老版本,写了rvcheck来帮忙检查版本。既然能够帮我们检查版本,自然能够帮忙升级。
使用rvcheck::update_all()
可以自动更新CRAN, Bioconductor和Github上的R包。其实可以放到系统任务里,每月自动更新一次,然后就可以完全不用管升级的事情。
ggtree provides many helper functions for manupulating phylogenetic trees and make it easy to explore tree structure visually.
Here, as examples, I used ggtree
to draw capital character G
and 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 G
and C
shapes of tree. I am thinking about using the G
shaped tree as ggtree
logo. Have fun with ggtree
:-)
OutbreakTools implements basic tools for the analysis of Disease Outbreaks.
It defines S4
class 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)
ggtree can parse many software outputs and the evolution evidences inferred by these software can be used directly for tree annotation. ggtree not only works as an infrastructure that enables evolutionary data that inferred by commonly used software packages to be used in R, but also serves as a general tree visualization and annotation tool for the R community as it supports many S3/S4 objects defined by other R packages.
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 theme
, 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 phyloseq
and ggplot2
.
MeSH (Medical Subject Headings) is the NLM (U.S. National Library of
Medicine) controlled vocabulary used to manually index articles for
MEDLINE/PubMed. MeSH is comprehensive life science vocabulary. MeSH has
19 categories and MeSH.db
contains 16 of them. That is:
Leading edge analysis reports Tags
to indicate the percentage of genes contributing to the enrichment score, List
to indicate where in the list the enrichment score is attained and Signal
for enrichment signal strength.
It would also be very interesting to get the core enriched genes that contribute to the enrichment.
Now DOSE, clusterProfiler and ReactomePA all support leading edge analysis and report core enriched genes.