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BMC Genomics. 2018 Jun 25;19(1):493. doi: 10.1186/s12864-018-4870-z.

WHAM!: a web-based visualization suite for user-defined analysis of metagenomic shotgun sequencing data.

Author information

1
Sackler Institute of Graduate Biomedical Sciences, New York School of Medicine, New York, NY, USA.
2
Division of Translational Medicine, Department of Medicine, New York School of Medicine, New York, NY, USA.
3
Department of Microbiology, New York School of Medicine, New York, NY, USA.
4
Sackler Institute of Graduate Biomedical Sciences, New York School of Medicine, New York, NY, USA. kelly.ruggles@nyumc.org.
5
Division of Translational Medicine, Department of Medicine, New York School of Medicine, New York, NY, USA. kelly.ruggles@nyumc.org.
6
Applied Bioinformatics Laboratories, New York School of Medicine, New York, NY, USA. kelly.ruggles@nyumc.org.

Abstract

BACKGROUND:

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. 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. The development of such platforms for this purpose is necessary to accelerate and streamline microbiome laboratory research.

RESULTS:

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. 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.

CONCLUSIONS:

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.

KEYWORDS:

DNA analysis; Data exploration; Expression analysis; Metatranscriptomic; Microbiome; RShiny

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