Signal Processing for Metagenomics: Extracting Information from the Soup

Title: Signal Processing for Metagenomics: Extracting Information from the Soup

Volume: 10 Issue: 7

Author(s): Gail L. Rosen, Bahrad A. Sokhansanj, Robi Polikar, Mary Ann Bruns, Jacob Russell, Elaine Garbarine, Steve Essinger and Non Yok

Affiliation:

Abstract: Traditionally, studies in microbial genomics have focused on single-genomes from cultured species, thereby limiting their focus to the small percentage of species that can be cultured outside their natural environment. Fortunately, recent advances in high-throughput sequencing and computational analyses have ushered in the new field of metagenomics, which aims to decode the genomes of microbes from natural communities without the need for cultivation. Although metagenomic studies have shed a great deal of insight into bacterial diversity and coding capacity, several computational challenges remain due to the massive size and complexity of metagenomic sequence data. Current tools and techniques are reviewed in this paper which address challenges in 1) genomic fragment annotation, 2) phylogenetic reconstruction, 3) functional classification of samples, and 4) interpreting complementary metaproteomics and metametabolomics data. Also surveyed are important applications of metagenomic studies, including microbial forensics and the roles of microbial communities in shaping human health and soil ecology.

Cite this article as:

Rosen L. Gail, Sokhansanj A. Bahrad, Polikar Robi, Bruns Ann Mary, Russell Jacob, Garbarine Elaine, Essinger Steve and Yok Non, Signal Processing for Metagenomics: Extracting Information from the Soup, Current Genomics 2009; 10 (7) . https://dx.doi.org/10.2174/138920209789208255