The metagenomics RAST server – a public resource for the automatic phylogenetic and functional analysis of metagenomes

The metagenomics RAST server – a public resource for the automatic phylogenetic and functional analysis of metagenomes

5/14/08 | F. Meyer, D. Paarmann, M. D'Souza, R. Olson, E. M. Glass, M. Kubal, T. Paczian, R. Stevens, A. Wilke, J. Wilkening, R. A. Edwards
The metagenomics RAST (mg-RAST) server is a public resource designed for the automated phylogenetic and functional analysis of metagenomes. It addresses the challenge of analyzing high-throughput, low-cost next-generation sequencing data by providing a high-performance computing pipeline. The server accepts raw sequence data in various formats, including 454 reads and Sanger sequences, and processes it through a modular framework that supports multiple data sources and analysis steps. Key features include automated functional assignments, phylogenetic and metabolic reconstructions, and comparative metagenomics tools. Users can upload data, control access to their datasets, and download results in various formats. The mg-RAST server is freely available, open-source, and aims to remove bottlenecks in metagenome sequence analysis by providing robust and flexible tools for researchers.The metagenomics RAST (mg-RAST) server is a public resource designed for the automated phylogenetic and functional analysis of metagenomes. It addresses the challenge of analyzing high-throughput, low-cost next-generation sequencing data by providing a high-performance computing pipeline. The server accepts raw sequence data in various formats, including 454 reads and Sanger sequences, and processes it through a modular framework that supports multiple data sources and analysis steps. Key features include automated functional assignments, phylogenetic and metabolic reconstructions, and comparative metagenomics tools. Users can upload data, control access to their datasets, and download results in various formats. The mg-RAST server is freely available, open-source, and aims to remove bottlenecks in metagenome sequence analysis by providing robust and flexible tools for researchers.
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