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1.We present an R package, GGTREE, which provides programmable visualization and annotation of phyloge- netic trees. 2. GGTREE can read more tree file formats than other softwares, including newick, nexus, NHX, phylip and jplace formats, and support visualization of phylo, multiphylo, phylo4, phylo4d, obkdata and phyloseq tree objects defined in other R packages. It can also extract the tree/branch/node-specific and other data from the analysis outputs of BEAST, EPA, HYPHY, PAML, PHYLODOG, PPLACER, R8S, RAXML and REVBAYES software, and allows using these data to annotate the tree. 3. The package allows colouring and annotation of a tree by numerical/categorical node attributes, manipulat- ing a tree by rotating, collapsing and zooming out clades, highlighting user selected clades or operational taxo- nomic units and exploration of a large tree by zooming into a selected portion. 4. A two-dimensional tree can be drawn by scaling the tree width based on an attribute of the nodes. A tree can be annotated with an associated numerical matrix (as a heat map), multiple sequence alignment, subplots or silhouette images. 5. The package GGTREE is released under the ARTISTIC-2.0 LICENSE. The source code and documents are freely available through BIOCONDUCTOR (

Summary: ChIPseeker is an R package for annotating ChIP-seq data analysis. It supports annotating ChIP peaks and provides functions to visualize ChIP peaks coverage over chromosomes and profiles of peaks binding to TSS regions. Comparison of ChIP peak profiles and annotation are also supported. Moreover, it supports evaluating significant overlap among ChIP-seq datasets. Currently, ChIPseeker contains 15 000 bed file information from GEO database. These datasets can be downloaded and compare with user's own data to explore significant overlap datasets for inferring co-regulation or transcription factor complex for further investigation.

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I am very glad to find that someone figure out how to use ggjoy with ggtree.

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.


I just discovered an interesting ggplot2 extension, 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.


I have 8 packages published within the Bioconductor project.

A new package treeio was included in BioC 3.5 release.


With ggtree (Yu et al. 2017), it is very easy to create phylomoji. Emoji is internally supported by ggtree.

Use emoji in taxa labels

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")


I have splitted ggtree to 2 packages, treeio and ggtree. Now ggtree is mainly focus on visualization and annotation, while treeio focus on parsing and exporting tree files. Here is a welcome message from treeio that you can convert ggtree output to tree object which can be exported as newick or nexus file if you want.

Thanks to ggplot2, output of ggtree is actually a ggplot object. The ggtree object can be rendered as graph by print method, but internally it is an object that contains data. treeio defines as.phylo and as.treedata to convert ggtree object to phylo or treedata object.




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.


emojifont is an implementation of using emoji font in both base and ‘ggplot2’ graphics.


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.


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


The clusterProfiler package implements methods to analyze and visualize functional profiles of genomic coordinates (supported by ChIPseeker), gene and gene clusters.


The semantic comparisons of Gene Ontology (GO) annotations provide quantitative ways to compute similarities between genes and gene groups, and have became important basis for many bioinformatics analysis approaches. GOSemSim is an R package for semantic similarity computation among GO terms, sets of GO terms, gene products and gene clusters. GOSemSim implemented five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively.


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