[Bioc 3.5] NEWS of my BioC packages

I have 8 packages published within the Bioconductor project.

A new package treeio was included in BioC 3.5 release.

[Bioc 34] NEWS of my BioC packages

I have 7 packages published within the Bioconductor project.

A new package meshes was included in BioC 3.4 release.


This package provides functions for pathway analysis based on REACTOME pathway database. It implements enrichment analysis, gene set enrichment analysis and several functions for visualization.

[Bioc 33] NEWS of my BioC packages

Today is my birthday and it happened to be the release day of Bioconductor 3.3. It’s again the time to reflect what I’ve done in the past year.

[Bioc 32] NEWS of my BioC packages

In BioC 3.2 release, all my packages including GOSemSim, clusterProfiler, DOSE, ReactomePA, and ChIPseeker switch from Sweave to R Markdown for package vignettes.


To make it consistent between GOSemSim and clusterProfiler, ‘worm’ was deprecated and instead we should use ‘celegans’. As usual, information content data was updated.

[Bioc 31] 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.

ggtree in Bioconductor 3.1

I am very glad that ggtree is now available via Bioconductor. This is my 6th Bioconductor package. ggtree now supports parsing output files from BEAST, PAML, HYPHY, EPA and PPLACER and can annotate phylogenetic tree directly using plot methods.


The ggtree package extending the ggplot2 package. It based on grammar of graphics and takes all the good parts of ggplot2. ggtree is designed for not only viewing phylogenetic tree but also displaying annotation data on the tree.


This package implements functions to retrieve the nearest genes around the peak, annotate genomic region of the peak, statstical methods for estimate the significance of overlap among ChIP peak data sets, and incorporate GEO database for user to compare their own dataset with those deposited in database. The comparison can be used to infer cooperative regulation and thus can be used to generate hypotheses. Several visualization functions are implemented to summarize the coverage of the peak experiment, average profile and heatmap of peaks binding to TSS regions, genomic annotation, distance to TSS, and overlap of peaks or genes.


This package implements five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively for measuring semantic similarities among DO terms and gene products. Enrichment analyses including hypergeometric model and gene set enrichment analysis are also implemented for discovering disease associations of high-throughput biological data.