Nucleic Acids ResearchBioinformaticsPeer-reviewed journal article
Metaviz: interactive statistical and visual analysis of metagenomic data
Justin WagneriD, Florin ChelaruiD, Jayaram KancherlaiD, Joseph Nathaniel PaulsoniD, Alexander Zhang, Victor FelixiD, Anup MahurkariD, Niklas ElmqvistiD, Héctor Corrada BravoiD
Abstract
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.
- assay: metagenomics
- research focus: database / resource
- research focus: benchmarking
- research focus: dimensionality reduction
- approach: statistical model
- approach: experimental assay
- Citations
- 42
- FWCI
- 1.60
- Field percentile
- top 16%
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