Arango-Argoty, GustavoSingh, GarhiHeath, Lenwood S.Pruden, AmyXiao, WeidongZhang, Liqing2017-03-082017-03-082016-09-151932-6203http://hdl.handle.net/10919/75498Metagenomics 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. Interpretationand 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. MetaStormoffers 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.? - ? (13) page(s)application/pdfCreative Commons Attribution 4.0 Internationalrna gene databasemicrobial communitysequencing datagut microbiomediversityevolutionalignmentecologytoolssoilArticle - Refereedhttps://doi.org/10.1371/journal.pone.0162442119Heath, LS [0000-0003-1608-431X]