Analysis of Metagenomics Data

Abstract

Improved sampling of diverse environments and advances in the develop- ment and application of next-generation sequencing technologies are accelerating the rate at which new metagenomes are produced. Over the past few years, the major chal- lenge associated with metagenomics has shifted from generating to analyzing sequences. Metagenomic analysis includes the identification, and functional and evo- lutionary analysis of the genomic sequences of a community of organisms. There are many challenges involved in the analysis of these data sets including sparse meta- data, a high volume of sequence data, genomic heterogeneity, and incomplete sequences. Because of the nature of metagenomic data, analysis is very complex and requires new approaches and significant compute resources. Recently, several com- putational systems and tools have been developed and applied to analyze their func- tional and phylogenetic composition. The metagenomics RAST server (MG-RAST) is a high-throughput system that has been built to provide high-performance computing to researchers interested in analyzing metagenomic data. It has removed one of the primary bottlenecks in metagenome sequence analysis, the availability of high-performance computing for annotating data.