An application of statistics to comparative metagenomics.

@article{citeulike:562245, abstract = {ABSTRACT: 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 are overrepresented in the Sargasso Sea and Acid Mine Drainage metagenome when compared to non-redundant databases were identified. CONCLUSIONS: 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.}, author = {Rodriguez-Brito, Beltran and Rohwer, Forest and Edwards, Robert }, citeulike-article-id = {562245}, doi = {10.1186/1471-2105-7-162}, issn = {1471-2105}, journal = {BMC Bioinformatics}, keywords = {metagenomic\_analysis, statistic}, month = {March}, number = {1}, posted-at = {2008-05-15 20:16:38}, priority = {2}, title = {An application of statistics to comparative metagenomics.}, url = {http://dx.doi.org/10.1186/1471-2105-7-162}, volume = {7}, year = {2006} }

TY - JOUR ID - citeulike:562245 L3 - citeulike-article-id:562245 TI - An application of statistics to comparative metagenomics. JF - BMC Bioinformatics VL - 7 IS - 1 SN - 1471-2105 N2 - ABSTRACT: 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 are overrepresented in the Sargasso Sea and Acid Mine Drainage metagenome when compared to non-redundant databases were identified. CONCLUSIONS: 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. KW - metagenomic_analysis KW - statistic AU - Rodriguez-Brito, Beltran AU - Rohwer, Forest AU - Edwards, Robert PY - 2006/03/20/ UR - http://dx.doi.org/10.1186/1471-2105-7-162 ER -