Category Archives: Biology

NEWS of my BioC packages


GOSemSim was first implemented in 2008 and published in Bioinformatics in 2010. It's now a mature package with no bugs found in the past half year. Only vignette and Information content data were updated.


clusterProfiler was developed in 2011 and published in OMICS in 2012.

I am very glad to find that clusterProfiler was presented in the book 'Bioinformatics with R Cookbook':

In this release, KEGG enrichment analysis (both hypergeometric and GSEA) now supports using latest online data and DAVID functional analysis is also supported. In addition, compareCluster function now supports formula interface like x ~ y + z; this feature was contributed by @dalloliogm.

Considering that many new users have problem of converting biological IDs, clusterProfiler contains a new function bitr, stands for Biological Id TranslatoR.
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an example of drawing beast tree using ggtree

FigTree is designed for viewing beast output as demonstrated by their example data:

BEAST output is well supported by ggtree and it's easy to reproduce such a tree view. ggtree supports parsing beast output by read.beast function. We can visualize the tree directly by using ggtree function. Since this is a time scale tree, we can set the parameter time_scale = TRUE and ggtree will parse the time and use it as branch length.
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DAVID functional analysis with clusterProfiler

clusterProfiler was used to visualize DAVID results in a paper published in BMC Genomics.

Some users told me that they may want to use DAVID at some circumstances. I think it maybe a good idea to make clusterProfiler supports DAVID, so that DAVID users can use visualization functions provided by clusterProfiler.
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DOSE: an R/Bioconductor package for Disease Ontology Semantic and Enrichment analysis

My R/Bioconductor package, DOSE, published in Bioinformatics.

DOSE: an R/Bioconductor package for Disease Ontology Semantic and Enrichment analysis
G Yu, LG Wang, GR Yan, QY He.
Bioinformatics 2015, 31(4):608-609
Received: 7 May 2014
Accepted: 14 October 2014
Online: 17 October 2014
DOI: 10.1093/bioinformatics/btu684

Summary: Disease ontology (DO) annotates human genes in the context of disease. DO is important annotation in translating molecular findings from high-throughput data to clinical relevance. DOSE is an R package providing semantic similarity computations among DO terms and genes which allows biologists to explore the similarities of diseases and of gene functions in disease perspective. Enrichment analyses including hypergeometric model and gene set enrichment analysis are also implemented to support discovering disease associations of high-throughput biological data. This allows biologists to verify disease relevance in a biological experiment and identify unexpected disease associations. Comparison among gene clusters is also supported.

Availability and implementation: DOSE is released under Artistic-2.0 License. The source code and documents are freely available through Bioconductor (

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[ggtree] updating a tree view using %<% operator

I am very exciting that I have received very positive feedback from Ahmed Moustafa and Simon Frost.

ggtree now has equipped with a lot of new features. This time, I would like to introduce the replace operator, %<%.

Suppose we have build a tree view using ggtree with multiple layers, we don't need to run the code again to build a new tree view with another tree. In ggtree, we provides an operator, %<%, for updating tree view.

?View Code RSPLUS
ggtree(rtree(15)) %< % rtree(30)

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