Metaviz

Metaviz facilitates interactive exploratory analysis of annotated microbiome taxonomic community profiles derived from marker gene sequencing and whole metagenome shotgun sequencing to support investigation of microbial community composition and associations with phenotypes.


Key Features:

  • Interactive visualizations: Provides interactive heatmaps, stacked bar charts, and scatter plots with linked updates across hierarchical taxonomic features.
  • Hierarchical data handling: Supports browsing and analysis of hierarchical metagenomic feature structures inherent to taxonomic community profiles.
  • Plugin framework: Enables extensibility for additional visualizations via d3.js.
  • Bioconductor integration: Interoperates with Bioconductor analysis tools through the metavizr R package.
  • Extensive dataset access: Includes access to metadata and profiles from over 7,000 microbiomes derived from published studies.

Scientific Applications:

  • Microbial ecology: Exploration of taxonomic composition and hierarchical relationships within microbial communities.
  • Human health and phenotype association: Comparative analysis of metagenomic samples to investigate associations between microbial communities and health or disease phenotypes.
  • Integrative analysis of published datasets: Reuse and comparative interrogation of large-scale microbiome datasets across studies.

Methodology:

Implements interactive visualization techniques and hierarchical taxonomic data browsing and interoperates with Bioconductor tools via the metavizr R package.

Topics

Details

Tool Type:
web application
Programming Languages:
JavaScript
Added:
8/6/2018
Last Updated:
12/10/2018

Operations

Data Inputs & Outputs

Publications

Wagner J, Chelaru F, Kancherla J, Paulson JN, Zhang A, Felix V, Mahurkar A, Elmqvist N, Corrada Bravo H. Metaviz: interactive statistical and visual analysis of metagenomic data. Nucleic Acids Research. 2018;46(6):2777-2787. doi:10.1093/nar/gky136. PMID:29529268. PMCID:PMC5887897.

PMID: 29529268
PMCID: PMC5887897
Funding: - National Institutes of Health: RO1GM114267, U54DK102556

Documentation

Links