PT - JOURNAL ARTICLE AU - Justin Wagner AU - Florin Chelaru AU - Jayaram Kancherla AU - Joseph N. Paulson AU - Victor Felix AU - Anup Mahurkar AU - Héctor Corrada Bravo TI - Metaviz: interactive statistical and visual analysis of metagenomic data AID - 10.1101/105205 DP - 2017 Jan 01 TA - bioRxiv PG - 105205 4099 - http://biorxiv.org/content/early/2017/02/02/105205.short 4100 - http://biorxiv.org/content/early/2017/02/02/105205.full AB - Along with the survey techniques of 16S rRNA amplicon and whole-metagenome shotgun sequencing, an array of tools exists for clustering, taxonomic annotation, normalization, and statistical analysis of microbiome sequencing results. Integrative and interactive visualization that enables researchers to perform exploratory analysis in this feature rich hierarchical data is an area of need. In this work, we present Metaviz, a web browser-based tool for interactive exploratory metagenomic data analysis. Metaviz can visualize abundance data served from an R session or a Python web service that queries a graph database. As metagenomic sequencing features have a hierarchy, we designed a novel navigation mechanism to explore this feature space. We visualize abundance counts with heatmaps and stacked bar plots that are dynamically updated as a user selects taxonomic features to inspect. Metaviz also supports common data exploration techniques, including PCA scatter plots to interpret variability in the dataset and alpha diversity boxplots for examining ecological community composition. The Metaviz application and documentation is hosted at http://www.metaviz.org.