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GenomeGraphs: integrated genomic data visualization with R

Steffen Durinck12*, James Bullard2*, Paul T Spellman1 and Sandrine Dudoit23

Author Affiliations

1 Life Sciences Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Rd, Berkeley, CA 94720, USA

2 Division of Biostatistics, School of Public Health, UC Berkeley, 101 Haviland Hall, Berkeley, CA 94720-7358, USA

3 Department of Statistics, UC Berkeley, 367 Evans Hall, Berkeley, CA 94720-3860, USA

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BMC Bioinformatics 2009, 10:2  doi:10.1186/1471-2105-10-2

Published: 6 January 2009



Biological studies involve a growing number of distinct high-throughput experiments to characterize samples of interest. There is a lack of methods to visualize these different genomic datasets in a versatile manner. In addition, genomic data analysis requires integrated visualization of experimental data along with constantly changing genomic annotation and statistical analyses.


We developed GenomeGraphs, as an add-on software package for the statistical programming environment R, to facilitate integrated visualization of genomic datasets. GenomeGraphs uses the biomaRt package to perform on-line annotation queries to Ensembl and translates these to gene/transcript structures in viewports of the grid graphics package. This allows genomic annotation to be plotted together with experimental data. GenomeGraphs can also be used to plot custom annotation tracks in combination with different experimental data types together in one plot using the same genomic coordinate system.


GenomeGraphs is a flexible and extensible software package which can be used to visualize a multitude of genomic datasets within the statistical programming environment R.