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Phylogeny-driven target selection for large-scale genome-sequencing (and other) projects

Overview of attention for article published in Environmental Microbiome, June 2013
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Title
Phylogeny-driven target selection for large-scale genome-sequencing (and other) projects
Published in
Environmental Microbiome, June 2013
DOI 10.4056/sigs.3446951
Pubmed ID
Authors

Markus Göker, Hans-Peter Klenk

Abstract

Despite the steadily decreasing costs of genome sequencing, prioritizing organisms for sequencing remains important in large-scale projects. Phylogeny-based selection is of interest to identify those organisms whose genomes can be expected to differ most from those that have already been sequenced. Here, we describe a method that infers a phylogenetic scoring independent of which set of organisms has previously been targeted, which is computationally simple and easy to apply in practice. The scoring itself, as well as pre- and post-processing of the data, is illustrated using two real-world examples in which the method has already been applied for selecting targets for genome sequencing. These projects are the JGI CSP Genomic Encyclopedia of Bacteria and Archaea phase I, targeting 1,000 type strains, and, on a smaller-scale, the phylogenomics of the Roseobacter clade. Potential artifacts of the method are discussed and compared to a selection approach based on the taxonomic classification.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 4%
Sweden 1 4%
Germany 1 4%
South Africa 1 4%
Unknown 24 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 36%
Student > Ph. D. Student 6 21%
Professor 2 7%
Student > Doctoral Student 2 7%
Professor > Associate Professor 2 7%
Other 3 11%
Unknown 3 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 61%
Biochemistry, Genetics and Molecular Biology 2 7%
Computer Science 2 7%
Immunology and Microbiology 2 7%
Unknown 5 18%
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 20 June 2013.
All research outputs
#20,655,488
of 25,371,288 outputs
Outputs from Environmental Microbiome
#579
of 786 outputs
Outputs of similar age
#160,105
of 209,857 outputs
Outputs of similar age from Environmental Microbiome
#12
of 15 outputs
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So far Altmetric has tracked 786 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 8th percentile – i.e., 8% of its peers scored the same or lower than it.
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