Sackler Institute of Graduate Biomedical Sciences, New York School of Medicine, New York, NY, USA.
Division of Translational Medicine, Department of Medicine, New York School of Medicine, New York, NY, USA.
BMC Genomics. 2018 Jun 25;19(1):493. doi: 10.1186/s12864-018-4870-z.
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.
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.
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.
生物医学专家和医疗专业人员对大型数据集(如鸟枪法宏基因组测序或表达数据)的探索仍然是科学发现过程中的主要瓶颈。尽管存在用于 16S 核糖体 RNA 测序分析的此类工具,但仍然缺乏用户友好的交互式可视化工作流程,难以轻松地进行数据探索和生成图形。因此,有必要为此目的开发此类平台,以加速和简化微生物组实验室研究。
我们开发了基于网络的交互式工具 Workflow Hub for Automated Metagenomic Exploration(WHAM!),用于对带注释的鸟枪法宏基因组和宏转录组数据集进行用户指导的数据可视化和统计分析。WHAM! 包括探索性和基于假设的基因和分类群搜索模块,用于可视化实验组之间微生物分类群和基因家族表达的差异,并创建具有出版物质量的图形,而无需使用命令行界面或内部生物信息学。
WHAM! 是用于下游宏基因组和宏转录组分析的交互式和可定制工具,提供了用户友好的界面,使微生物组和生态专家能够轻松地进行数据探索,从而促进多维和大规模数据集的发现。