Journal Paper

#56 

@article{Wagner2018, title={Metaviz: interactive statistical and visual analysis of metagenomic data}, author={Justin Wagner and Florin Chelaru and Jayaram Kancherla and Joseph N. Paulson and Alexander Zhang and Victor Felix and Anup Mahurkar and Niklas Elmqvist and Hector Corrada Bravo}, url={https://academic.oup.com/nar/article-pdf/46/6/2777/24526301/gky136.pdf}, year={2018}, date={2018-03-06}, journal={Nucleic Acids Research}, volume={46}, number={6}, pages={2777--2787}, abstract={Large studies profiling microbial communities and their association with healthy or disease phenotypes are now commonplace. Processed data from many of these studies are publicly available but significant effort is required for users to effectively organize, explore and integrate it, limiting the utility of these rich data resources. Effective integrative and interactive visual and statistical tools to analyze many metagenomic samples can greatly increase the value of these data for researchers. We present Metaviz, a tool for interactive exploratory data analysis of annotated microbiome taxonomic community profiles derived from marker gene or whole metagenome shotgun sequencing. Metaviz is uniquely designed to address the challenge of browsing the hierarchical structure of metagenomic data features while rendering visualizations of data values that are dynamically updated in response to user navigation. We use Metaviz to provide the UMD Metagenome Browser web service, allowing users to browse and explore data for more than 7000 microbiomes from published studies. Users can also deploy Metaviz as a web service, or use it to analyze data through the metavizr package to interoperate with state-of-the-art analysis tools available through Bioconductor. Metaviz is free and open source with the code, documentation and tutorials publicly accessible.}, keywords={}, }