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Inferring Phylogenies from RAD Sequence Data

Overview of attention for article published in PLOS ONE, April 2012
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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 (94th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

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2 blogs
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7 X users
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1 Wikipedia page

Citations

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277 Dimensions

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687 Mendeley
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3 CiteULike
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Title
Inferring Phylogenies from RAD Sequence Data
Published in
PLOS ONE, April 2012
DOI 10.1371/journal.pone.0033394
Pubmed ID
Authors

Benjamin E. R. Rubin, Richard H. Ree, Corrie S. Moreau

Abstract

Reduced-representation genome sequencing represents a new source of data for systematics, and its potential utility in interspecific phylogeny reconstruction has not yet been explored. One approach that seems especially promising is the use of inexpensive short-read technologies (e.g., Illumina, SOLiD) to sequence restriction-site associated DNA (RAD)--the regions of the genome that flank the recognition sites of restriction enzymes. In this study, we simulated the collection of RAD sequences from sequenced genomes of different taxa (Drosophila, mammals, and yeasts) and developed a proof-of-concept workflow to test whether informative data could be extracted and used to accurately reconstruct "known" phylogenies of species within each group. The workflow consists of three basic steps: first, sequences are clustered by similarity to estimate orthology; second, clusters are filtered by taxonomic coverage; and third, they are aligned and concatenated for "total evidence" phylogenetic analysis. We evaluated the performance of clustering and filtering parameters by comparing the resulting topologies with well-supported reference trees and we were able to identify conditions under which the reference tree was inferred with high support. For Drosophila, whole genome alignments allowed us to directly evaluate which parameters most consistently recovered orthologous sequences. For the parameter ranges explored, we recovered the best results at the low ends of sequence similarity and taxonomic representation of loci; these generated the largest supermatrices with the highest proportion of missing data. Applications of the method to mammals and yeasts were less successful, which we suggest may be due partly to their much deeper evolutionary divergence times compared to Drosophila (crown ages of approximately 100 and 300 versus 60 Mya, respectively). RAD sequences thus appear to hold promise for reconstructing phylogenetic relationships in younger clades in which sufficient numbers of orthologous restriction sites are retained across species.

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Geographical breakdown

Country Count As %
United States 25 4%
Brazil 5 <1%
Switzerland 4 <1%
France 3 <1%
United Kingdom 3 <1%
Australia 3 <1%
Netherlands 2 <1%
Canada 2 <1%
Belgium 2 <1%
Other 13 2%
Unknown 625 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 224 33%
Researcher 139 20%
Student > Master 77 11%
Student > Doctoral Student 40 6%
Student > Bachelor 40 6%
Other 111 16%
Unknown 56 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 481 70%
Biochemistry, Genetics and Molecular Biology 68 10%
Environmental Science 33 5%
Computer Science 10 1%
Earth and Planetary Sciences 7 1%
Other 15 2%
Unknown 73 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 27 February 2017.
All research outputs
#1,431,730
of 22,664,267 outputs
Outputs from PLOS ONE
#18,738
of 193,506 outputs
Outputs of similar age
#8,471
of 161,502 outputs
Outputs of similar age from PLOS ONE
#312
of 3,696 outputs
Altmetric has tracked 22,664,267 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 193,506 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one has done particularly well, scoring higher than 90% 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 161,502 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 3,696 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 91% of its contemporaries.