Arango-Argoty Gustavo, Singh Gargi, Heath Lenwood S, Pruden Amy, Xiao Weidong, Zhang Liqing
Department of Computer Science, Virginia Tech, Blacksburg, Virginia, United States of America.
Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India.
PLoS One. 2016 Sep 15;11(9):e0162442. doi: 10.1371/journal.pone.0162442. eCollection 2016.
Metagenomics is a trending research area, calling for the need to analyze large quantities of data generated from next generation DNA sequencing technologies. The need to store, retrieve, analyze, share, and visualize such data challenges current online computational systems. Interpretation and annotation of specific information is especially a challenge for metagenomic data sets derived from environmental samples, because current annotation systems only offer broad classification of microbial diversity and function. Moreover, existing resources are not configured to readily address common questions relevant to environmental systems. Here we developed a new online user-friendly metagenomic analysis server called MetaStorm (http://bench.cs.vt.edu/MetaStorm/), which facilitates customization of computational analysis for metagenomic data sets. Users can upload their own reference databases to tailor the metagenomics annotation to focus on various taxonomic and functional gene markers of interest. MetaStorm offers two major analysis pipelines: an assembly-based annotation pipeline and the standard read annotation pipeline used by existing web servers. These pipelines can be selected individually or together. Overall, MetaStorm provides enhanced interactive visualization to allow researchers to explore and manipulate taxonomy and functional annotation at various levels of resolution.
宏基因组学是一个热门的研究领域，这就需要对下一代DNA测序技术产生的大量数据进行分析。存储、检索、分析、共享和可视化这些数据的需求给当前的在线计算系统带来了挑战。对于源自环境样本的宏基因组数据集而言，特定信息的解读和注释尤其具有挑战性，因为当前的注释系统仅能对微生物多样性和功能进行宽泛分类。此外，现有资源并未配置成能够轻松解决与环境系统相关的常见问题。在此，我们开发了一个名为MetaStorm（http://bench.cs.vt.edu/MetaStorm/）的新型在线用户友好型宏基因组分析服务器，它有助于对宏基因组数据集的计算分析进行定制。用户可以上传自己的参考数据库，以定制宏基因组注释，从而专注于感兴趣的各种分类学和功能基因标记。MetaStorm提供两种主要的分析管道：基于组装的注释管道和现有网络服务器使用的标准读段注释管道。这些管道可以单独选择或一起选择。总体而言，MetaStorm提供了增强的交互式可视化功能，使研究人员能够在不同分辨率水平上探索和操作分类学和功能注释。
