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ezTree: an automated pipeline for identifying phylogenetic marker genes and inferring evolutionary relationships among uncultivated prokaryotic draft genomes

Overview of attention for article published in BMC Genomics, January 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

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Title
ezTree: an automated pipeline for identifying phylogenetic marker genes and inferring evolutionary relationships among uncultivated prokaryotic draft genomes
Published in
BMC Genomics, January 2018
DOI 10.1186/s12864-017-4327-9
Pubmed ID
Authors

Yu-Wei Wu

Abstract

Inferring phylogenetic trees for newly recovered genomes from metagenomic samples is very useful in determining the identities of uncultivated microorganisms. Even though 16S ribosomal RNA small subunit genes have been established as "gold standard" markers for inferring phylogenetic trees, they usually cannot be assembled very well in metagenomes due to shared regions among 16S genes. Using single-copy marker genes to build genome trees has become increasingly popular for uncultivated species. Predefined marker gene sets were discovered and have been applied in various genomic studies; however these gene sets might not be adequate for novel, uncultivated, draft, or incomplete genomes. The automatic identification of marker gene sets among a set of genomes with different assembly qualities has thus become a very important task for inferring reliable phylogenetic relationships for microbial populations. A computational pipeline, ezTree, was developed to automatically identify single-copy marker genes for a group of genomes and build phylogenetic trees from the marker genes. Testing ezTree on a group of proteobacteria species revealed that ezTree was highly effective in pinpointing marker genes and constructing reliable trees for different groups of bacterial genomes. Applying ezTree to genomes that were recently recovered from metagenomes also showed that ezTree can help elucidate taxonomic relationships among newly recovered genomes and existing ones. The development of ezTree can help scientists build reliable phylogenetic trees for uncultivated species retrieved from environmental samples. The uncovered single-copy marker genes may also provide crucial hints for understanding shared features of a group of microbes. The ezTree pipeline is freely available at https://github.com/yuwwu/ezTree under a GNU GPLv3 license.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 112 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 24%
Student > Master 20 18%
Researcher 16 14%
Student > Bachelor 11 10%
Student > Postgraduate 7 6%
Other 15 13%
Unknown 16 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 37 33%
Biochemistry, Genetics and Molecular Biology 24 21%
Immunology and Microbiology 9 8%
Computer Science 6 5%
Environmental Science 6 5%
Other 10 9%
Unknown 20 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 07 March 2018.
All research outputs
#2,654,171
of 25,364,603 outputs
Outputs from BMC Genomics
#760
of 11,244 outputs
Outputs of similar age
#59,551
of 451,197 outputs
Outputs of similar age from BMC Genomics
#20
of 207 outputs
Altmetric has tracked 25,364,603 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 451,197 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 207 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.