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. 2011 Sep 7:12:444.
doi: 10.1186/1471-2164-12-444.

WebMGA: a customizable web server for fast metagenomic sequence analysis

Sitao Wu  1 , Zhengwei Zhu, Liming Fu, Beifang Niu, Weizhong Li
Affiliations

WebMGA: a customizable web server for fast metagenomic sequence analysis

Sitao Wu et al. BMC Genomics. .

Abstract

Background: The new field of metagenomics studies microorganism communities by culture-independent sequencing. With the advances in next-generation sequencing techniques, researchers are facing tremendous challenges in metagenomic data analysis due to huge quantity and high complexity of sequence data. Analyzing large datasets is extremely time-consuming; also metagenomic annotation involves a wide range of computational tools, which are difficult to be installed and maintained by common users. The tools provided by the few available web servers are also limited and have various constraints such as login requirement, long waiting time, inability to configure pipelines etc.

Results: We developed WebMGA, a customizable web server for fast metagenomic analysis. WebMGA includes over 20 commonly used tools such as ORF calling, sequence clustering, quality control of raw reads, removal of sequencing artifacts and contaminations, taxonomic analysis, functional annotation etc. WebMGA provides users with rapid metagenomic data analysis using fast and effective tools, which have been implemented to run in parallel on our local computer cluster. Users can access WebMGA through web browsers or programming scripts to perform individual analysis or to configure and run customized pipelines. WebMGA is freely available at http://weizhongli-lab.org/metagenomic-analysis.

Conclusions: WebMGA offers to researchers many fast and unique tools and great flexibility for complex metagenomic data analysis.

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Figures

Figure 1
Figure 1
Illustration of WebMGA and its metagenomic analysis functions. The major input of WebMGA is either a DNA sequence file or a protein sequence file. A user can run a single analysis at a time such as to prediction ORFs from the uploaded DNA sequences. A user can also use a script to call WebMGA to run multiple analyses or run a pipeline where one job can use the output of another job.
Figure 2
Figure 2
A screenshot and examples of output results of WebMGA. (a) A screenshot of WebMGA server (b) A plot of distribution of clusters by CD-HIT (c) COG annotation results are in several "TAB" delimited text files, which can be easily viewed locally. (d) A plot of length distribution by sequence statistical tool
Figure 3
Figure 3
A simple example pipeline configured with tools in WebMGA.
See this image and copyright information in PMC

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