Evidence map›Paper›PMID 20011103›Full record

SynthesisPLoS computational biology2009

The GAAS metagenomic tool and its estimations of viral and microbial average genome size in four major biomes.

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 and 18 more

Abstract readMeta-Analysis
In one paragraph

Synthesis in PLoS computational biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 105 papers.

0numbers the graph read from it
0cells of the map it votes in
105citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

105 citing papers in PubMed.

  1. International journal of systematic and evolutionary microbiology · 2025
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  19. Assessing Species Diversity Using Metavirome Data: Methods and Challenges.Computational and structural biotechnology journal · 2017
    Review
  20. Article

45 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

28 authors.

Florent E AnglyBiology Department, San Diego State University, San Diego, California, United States of America. forent.angly@gmail.com
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

Funding

Alcohol-induced epigenetic alterations in human stem cellsR01AA021301 · NIAAA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI KIM, YONG · 2011 to 2013
$1.0M
NIAAA NIH HHS R01 AA021301
6 · The paper itself

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.

Indexed as

Genome, BacterialGenome, ViralSoftware DesignDatabases, Nucleic AcidMetagenomicsSequence Analysis, DNA

Identifiers

PMID20011103
PMCPMC2781106

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.