However, other platforms such as QIIME2 have recognized the utility of command line independence and user-defined exploration of sequencing data. Requiring users to specify the feature of interest hinders exploration of the data set in its entirety. While HUMAnN2 includes a visualization script to generate relative abundance plots for a particular pathway or gene family of interest, users are limited in figure customization and must use the command line. However, both of these tools have limitations for downstream visualization and user-based data exploration. Two widely used tools, HUMANn2 and QIIME2, provide extensive frameworks for gene annotation and taxonomic analysis, respectively. Further because of the size and density of information, exploration of the data presents an even more overwhelming task for experimentalists, inhibiting data-driven discovery.Ĭoncurrently with the increasing interest in the field, many of the tools described above have been employed to analyze and characterize the human microbiome. Researchers then must sift through the data for their genes of interest to test their stated hypotheses. Output formats from annotation pipelines are typically cumbersome tables and large matrices of genes, assigned taxa, and abundance or expression levels. While these applications provide high quality functional and taxonomic annotations, a computational hurdle still exists between the data output and biologically interpretable results. WHAM! is an interactive and customizable tool for downstream metagenomic and metatranscriptomic analysis providing a user-friendly interface allowing for easy data exploration by microbiome and ecological experts to facilitate discovery in multi-dimensional and large-scale data sets.Īs metagenomic and metatranscriptomic shotgun sequencing data become both less expensive to generate and more readily available, researchers have turned to automated pipelines such as MetaPhlAn, HUMAnN2 MEGAN and SAMSA for annotation and analysis. WHAM! includes exploratory and hypothesis-based gene and taxa search modules for visualizing differences in microbial taxa and gene family expression across experimental groups, and for creating publication quality figures without the need for command line interface or in-house bioinformatics. We developed the Workflow Hub for Automated Metagenomic Exploration (WHAM!) as a web-based interactive tool capable of user-directed data visualization and statistical analysis of annotated shotgun metagenomic and metatranscriptomic data sets. The development of such platforms for this purpose is necessary to accelerate and streamline microbiome laboratory research.
Although tools for this purpose exist for 16S ribosomal RNA sequencing analysis, there is a growing but still insufficient number of user-friendly interactive visualization workflows for easy data exploration and figure generation. Exploration of large data sets, such as shotgun metagenomic sequence or expression data, by biomedical experts and medical professionals remains as a major bottleneck in the scientific discovery process.
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