Methodology article
An application of statistics to comparative metagenomics
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* Corresponding author: Robert A Edwards redwards@salmonella.org
1 Computational Science Research Center, San Diego State University, San Diego, USA
2 Center for Microbial Sciences, San Diego State University, San Diego, USA
3 Department of Biology, San Diego State University, San Diego, USA
4 Fellowship for Interpretation of Genomes, Burr Ridge, USA
BMC Bioinformatics 2006, 7:162 doi:10.1186/1471-2105-7-162
Published: 20 March 2006Abstract
Background
Metagenomics, sequence analyses of genomic DNA isolated directly from the environments, can be used to identify organisms and model community dynamics of a particular ecosystem. Metagenomics also has the potential to identify significantly different metabolic potential in different environments.
Results
Here we use a statistical method to compare curated subsystems, to predict the physiology, metabolism, and ecology from metagenomes. This approach can be used to identify those subsystems that are significantly different between metagenome sequences. Subsystems that were overrepresented in the Sargasso Sea and Acid Mine Drainage metagenome when compared to non-redundant databases were identified.
Conclusion
The methodology described herein applies statistics to the comparisons of metabolic potential in metagenomes. This analysis reveals those subsystems that are more, or less, represented in the different environments that are compared. These differences in metabolic potential lead to several testable hypotheses about physiology and metabolism of microbes from these ecosystems.