Literature DB >> 20336158

Average genome size: a potential source of bias in comparative metagenomics.

Bánk Beszteri1, Ben Temperton, Stephan Frickenhaus, Stephen J Giovannoni.   

Abstract

In gene-centric comparative metagenomics, differences in observed relative gene abundances among samples are often assumed to reflect the biological importance of individual genes in different habitats. Statistical tests and data mining for genes that represent habitat-specific adaptations are frequently based on this measure. We demonstrate that this measure is biased by the average genome size of the communities sampled. Average genome sizes can be estimated from the metagenomic data themselves, and taken into account in comparative analyses. We suggest that this would enable ecologically more meaningful comparisons, especially when the average genome sizes of compared communities differ substantially. We illustrate the influence of average genome-size differences on comparative analyses, with an example to highlight the need for further exploration of this bias.

Mesh:

Year:  2010        PMID: 20336158     DOI: 10.1038/ismej.2010.29

Source DB:  PubMed          Journal:  ISME J        ISSN: 1751-7362            Impact factor:   10.302


  31 in total

1.  Metagenomic analyses of drinking water receiving different disinfection treatments.

Authors:  Vicente Gomez-Alvarez; Randy P Revetta; Jorge W Santo Domingo
Journal:  Appl Environ Microbiol       Date:  2012-06-22       Impact factor: 4.792

2.  An integrative study of a meromictic lake ecosystem in Antarctica.

Authors:  Federico M Lauro; Matthew Z DeMaere; Sheree Yau; Mark V Brown; Charmaine Ng; David Wilkins; Mark J Raftery; John A E Gibson; Cynthia Andrews-Pfannkoch; Matthew Lewis; Jeffrey M Hoffman; Torsten Thomas; Ricardo Cavicchioli
Journal:  ISME J       Date:  2010-12-02       Impact factor: 10.302

3.  Potential for phosphite and phosphonate utilization by Prochlorococcus.

Authors:  Roi Feingersch; Alon Philosof; Tom Mejuch; Fabian Glaser; Onit Alalouf; Yuval Shoham; Oded Béjà
Journal:  ISME J       Date:  2011-10-20       Impact factor: 10.302

4.  Quantitative metagenomic analyses based on average genome size normalization.

Authors:  Jeremy A Frank; Søren J Sørensen
Journal:  Appl Environ Microbiol       Date:  2011-02-11       Impact factor: 4.792

Review 5.  Survey of (Meta)genomic Approaches for Understanding Microbial Community Dynamics.

Authors:  Anukriti Sharma; Rup Lal
Journal:  Indian J Microbiol       Date:  2016-11-11       Impact factor: 2.461

Review 6.  Shotgun metagenomics, from sampling to analysis.

Authors:  Christopher Quince; Alan W Walker; Jared T Simpson; Nicholas J Loman; Nicola Segata
Journal:  Nat Biotechnol       Date:  2017-09-12       Impact factor: 54.908

7.  Accurate read-based metagenome characterization using a hierarchical suite of unique signatures.

Authors:  Tracey Allen K Freitas; Po-E Li; Matthew B Scholz; Patrick S G Chain
Journal:  Nucleic Acids Res       Date:  2015-03-12       Impact factor: 16.971

Review 8.  Toward Accurate and Quantitative Comparative Metagenomics.

Authors:  Stephen Nayfach; Katherine S Pollard
Journal:  Cell       Date:  2016-08-25       Impact factor: 41.582

9.  Metagenome analyses of corroded concrete wastewater pipe biofilms reveal a complex microbial system.

Authors:  Vicente Gomez-Alvarez; Randy P Revetta; Jorge W Santo Domingo
Journal:  BMC Microbiol       Date:  2012-06-22       Impact factor: 3.605

Review 10.  Functional assignment of metagenomic data: challenges and applications.

Authors:  Tulika Prakash; Todd D Taylor
Journal:  Brief Bioinform       Date:  2012-07-06       Impact factor: 11.622

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