Users can select the reference database to analyze and all the tables in text format can be downloaded. A Functional annotation is depicted by a pie chart, where the user can select the database to visualize.
B Sample comparison visualization using stacked bars for both taxonomy and function. C interactive heat map visualization where users can click on the branches to zoom over the related functions or taxas. Visualization techniques employed by MetaStorm include: heat maps, stacked bars, and interactive trees taxonomy annotation. As for single sample visualization, the response tree shows relative abundance for each node taxa and also for each taxonomic hierarchical level, allowing a high level of specificity.
From the home page, the user can access descriptions of all the recently listed public projects and the reference databases that other users submitted. A search tool is available for users to identify potential sets of reference sequences that can match their analysis.
Expectedly, small customized databases will report results faster than full reference databases. A novice user can use this database for analysis and jump to the specific biological problem, thus saving the computing time.
Moreover, the search tool enables users to find similar existing metagenome samples in MetaStorm public ones and include them for more comprehensive comparison studies. Comparison across different samples is made feasible by the normalization criteria implemented in MetaStorm.
Finally, all the raw and generated files for the metagenomic analysis can be downloaded in a variety of formats by clicking on the download button of each section in the visualization page. Compared to other metagenomic resources, such as MG-RAST and EBI-metagenomics, MetaStorm extends the analysis and visualization of metagenomic samples by: 1 adding a fully developed assembly-based annotation pipeline, in addition to the read matching pipeline deployed by these Web servers; 2 offering a customized analysis where the user can select and upload reference databases, which enables focus on specific genes of interest as well as inter-project comparison; and 3 interactive visualization capabilities, including an interactive taxonomic tree, which permit users to interrogate and compare specific aspects of the sequence data.
MetaStorm includes a wide variety of databases used for metagenomics analysis section customizable reference database. Those databases have been used as default by several current metagenomics resources. While the assembly pipeline implemented by MetaStorm is similar to that of the MetaHIT pipeline [ 26 ], it incorporates a more meaningful relative abundance determination in which copies are normalized to 16S rRNA gene copies [ 30 ].
Normalization enables comparison across multiple metagenomics data sets, including those generated by external labs, empowering researchers to address broad. This last feature is particularly promising for the future applicability of the MetaStorm server. MetaStorm is a free and public metagenomics resource that enables a more specific user customization through various improvements of visualization, data management, and user interactivity.
MetaStorm offers two main metagenomic analysis pipelines: the read matching pipeline similar to the current web resources and the assembly pipeline. MetaStorm, unlike any other web resources, incorporates user reference customization, which will help to streamline the annotation process when a research hypothesis requires specific and customized databases. Data curation: GA GS. Formal analysis: GA. Funding acquisition: AP.
Investigation: GA. Methodology: GA GS. Project administration: LZ. Resources: GA GS. Software: GA. Supervision: LZ. Validation: GA GS. Visualization: GS GA. Writing — original draft: GA. Browse Subject Areas? Click through the PLOS taxonomy to find articles in your field.
Abstract Metagenomics is a trending research area, calling for the need to analyze large quantities of data generated from next generation DNA sequencing technologies. Introduction The field of metagenomics has arisen following the advent of next-generation DNA sequencing. Materials and Methods Raw data is submitted to the MetaStorm server via a user-friendly web interface. Reference database Apart from a set of standard databases e. Download: PPT.
Table 1. Default reference databases provided by the MetaStorm Web service. Web-based submission Submission of metagenomic data is made by an interactive web interface Fig 1. Analysis pipeline Once stored in the MetaStorm server, raw reads are queued for taxonomic and functional annotations.
Assembly pipeline. Assembly: IDBA-UD [ 36 ] is a widely used metagenome assembler that has demonstrated consistent production of high quality scaffolds [ 37 , 38 , 39 ]. MetaStorm uses the default parameters. Gene prediction: Once a set of scaffolds are assembled, PRODIGAL [ 40 ] metagenomics version , a microbial gene finding program, is deployed to predict genes within each scaffold. Note that the taxonomy profile is computed based on the abundance of predicted genes, not the number of reads.
A set of marker genes processed by the MetaPhlAn2 [ 45 ] pipeline. This technique is included because whole genome sequencing samples typically contain very low 16S rRNA sequence content [ 26 , 27 , 45 ]. The reference sequence databases for functional annotation depend on the user criteria. For instance, a user interested in antibiotic resistance genes may prefer to run the analysis over the CARD database [ 31 ], whereas a project related to the degradation process may use the CAZy database [ 47 ].
Read matching pipeline. Sample normalization and comparison. MetaStorm implement three different normalization techniques as follows: Scaling : Normalize the number of matches obtained per sample, with relative abundance between 0 and Relative to 16S rRNAs : We use the normalization concept described in [ 30 ], which defines the relative abundance as the copy of a functional gene per copy of 16S rRNA genes.
Visualization of taxonomic abundance MetaStorm offers interactive visualization, allowing users to see in detail the main features of the sequence make-up of each sample. Visualization of functional abundance Functional relative abundance is described by a set of interactive pie charts and bar plots Fig 4A that relate functional categories with the genes involved in each category. Visualization of sample comparison Visualization techniques employed by MetaStorm include: heat maps, stacked bars, and interactive trees taxonomy annotation.
Results and Discussion Compared to other metagenomic resources, such as MG-RAST and EBI-metagenomics, MetaStorm extends the analysis and visualization of metagenomic samples by: 1 adding a fully developed assembly-based annotation pipeline, in addition to the read matching pipeline deployed by these Web servers; 2 offering a customized analysis where the user can select and upload reference databases, which enables focus on specific genes of interest as well as inter-project comparison; and 3 interactive visualization capabilities, including an interactive taxonomic tree, which permit users to interrogate and compare specific aspects of the sequence data.
Conclusion MetaStorm is a free and public metagenomics resource that enables a more specific user customization through various improvements of visualization, data management, and user interactivity.
References 1. Walter J, Ley R. The human gut microbiome: ecology and recent evolutionary changes. Annual review of microbiology. Metagenomic analysis of the human distal gut microbiome.
A metagenome-wide association study of gut microbiota in type 2 diabetes. Comparative metagenomics of bathypelagic plankton and bottom sediment from the Sea of Marmara. The ISME journal. Global ocean sampling collection. PLoS biol. Windows Users' choice Provision software download Provision software download Most people looking for Provision software downloaded: ProVision. TeraTerm Pro. ProVision Workbench. Refrig for Windows. Languages Online - Memory Game Maker. Avaya ProVision. Avaya Integrated Management Administration Tools.
Twitter Facebook. What I neglected to state was that I was trying using the provided conversion utility. Doing the conversion manually is much more effective, but you have to know how to use Metastorm BPM e-work very well to do so. We have come across a Metastorm ProVision forum. Jerome, thanks for the link to the forum. Is there anyone from Metastorm involved in this forum, or is it just customer and other interested parties?
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