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The GAAS Metagenomic Tool and Its Estimations of Viral and Microbial Average Genome Size in Four Major Biomes

Overview of attention for article published in PLoS Computational Biology, December 2009
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Title
The GAAS Metagenomic Tool and Its Estimations of Viral and Microbial Average Genome Size in Four Major Biomes
Published in
PLoS Computational Biology, December 2009
DOI 10.1371/journal.pcbi.1000593
Pubmed ID
Authors

Florent E. Angly, Dana Willner, Alejandra Prieto-Davó, Robert A. Edwards, Robert Schmieder, Rebecca Vega-Thurber, Dionysios A. Antonopoulos, Katie Barott, Matthew T. Cottrell, Christelle Desnues, Elizabeth A. Dinsdale, Mike Furlan, Matthew Haynes, Matthew R. Henn, Yongfei Hu, David L. Kirchman, Tracey McDole, John D. McPherson, Folker Meyer, R. Michael Miller, Egbert Mundt, Robert K. Naviaux, Beltran Rodriguez-Mueller, Rick Stevens, Linda Wegley, Lixin Zhang, Baoli Zhu, Forest Rohwer

Abstract

Metagenomic studies characterize both the composition and diversity of uncultured viral and microbial communities. BLAST-based comparisons have typically been used for such analyses; however, sampling biases, high percentages of unknown sequences, and the use of arbitrary thresholds to find significant similarities can decrease the accuracy and validity of estimates. Here, we present Genome relative Abundance and Average Size (GAAS), a complete software package that provides improved estimates of community composition and average genome length for metagenomes in both textual and graphical formats. GAAS implements a novel methodology to control for sampling bias via length normalization, to adjust for multiple BLAST similarities by similarity weighting, and to select significant similarities using relative alignment lengths. In benchmark tests, the GAAS method was robust to both high percentages of unknown sequences and to variations in metagenomic sequence read lengths. Re-analysis of the Sargasso Sea virome using GAAS indicated that standard methodologies for metagenomic analysis may dramatically underestimate the abundance and importance of organisms with small genomes in environmental systems. Using GAAS, we conducted a meta-analysis of microbial and viral average genome lengths in over 150 metagenomes from four biomes to determine whether genome lengths vary consistently between and within biomes, and between microbial and viral communities from the same environment. Significant differences between biomes and within aquatic sub-biomes (oceans, hypersaline systems, freshwater, and microbialites) suggested that average genome length is a fundamental property of environments driven by factors at the sub-biome level. The behavior of paired viral and microbial metagenomes from the same environment indicated that microbial and viral average genome sizes are independent of each other, but indicative of community responses to stressors and environmental conditions.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 385 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 19 5%
Brazil 8 2%
Canada 4 1%
Belgium 3 <1%
Germany 3 <1%
Sweden 3 <1%
France 2 <1%
South Africa 2 <1%
United Kingdom 2 <1%
Other 14 4%
Unknown 325 84%

Demographic breakdown

Readers by professional status Count As %
Researcher 103 27%
Student > Ph. D. Student 98 25%
Student > Master 44 11%
Student > Bachelor 23 6%
Professor > Associate Professor 21 5%
Other 64 17%
Unknown 32 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 227 59%
Biochemistry, Genetics and Molecular Biology 36 9%
Environmental Science 21 5%
Computer Science 14 4%
Immunology and Microbiology 12 3%
Other 28 7%
Unknown 47 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 November 2014.
All research outputs
#17,302,400
of 25,394,764 outputs
Outputs from PLoS Computational Biology
#7,481
of 8,964 outputs
Outputs of similar age
#146,876
of 176,075 outputs
Outputs of similar age from PLoS Computational Biology
#46
of 55 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
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We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.