Genome data visualizations
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Please cite: "Skidmore et al. 2016 GenVisR: Genomic Visualizations in R Bioinformatics 32, 3012-3014" pubmed


Intuitively visualizing and interpreting data from high-throughput genomic technologies continues to be challenging. "Genomic Visualizations in R" (GenVisR) attempts to alleviate this burden by providing highly customizable publication-quality graphics supporting multiple species and focused primarily on a cohort level (i.e., multiple samples/patients). GenVisR attempts to maintain a high degree of flexibility while leveraging the abilities of ggplot2 and bioconductor to achieve this goal.

Install from Bioconductor

For the majority of users we recommend installing GenVisR from the release branch of Bioconductor, Installation instructions using this method can be found on the GenVisR landing page on Bioconductor.

Please note that GenVisR imports a few packages that have "system requirements", in most cases these requirements will already be installed. If they are not please follow the instructions to install these packages given in the R terminal. Briefly these packages are: "libcurl4-openssl-dev" and "libxml2-dev"


Development for GenVisR occurs on the griffith lab github repository available here. For users wishing to contribute to development we recommend cloning the GenVisR repo there and submitting a pull request. Please note that development occurs on the R version that will be available at each Bioconductor release cycle. This ensures that GenVisR will be stable for each Bioconductor release but it may necessitate developers download R-devel.

We also encourage users to report bugs and suggest enhancements to GenVisR on the github issue page available here:

To install the latest development version of GenVisR (not recommended for most users):

# install and load devtools package

# install GenVisR from github


Documentation for GenVisR can be found on the bioconductor landing page in the form of vignettes available here GenVisR. Tutorials can also be found on Vignettes can also be viewed from within R.

# view vignettes