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Double Digest RADseq: An Inexpensive Method for De Novo SNP Discovery and Genotyping in Model and Non-Model Species

Overview of attention for article published in PLOS ONE, May 2012
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Citations

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3884 Mendeley
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Title
Double Digest RADseq: An Inexpensive Method for De Novo SNP Discovery and Genotyping in Model and Non-Model Species
Published in
PLOS ONE, May 2012
DOI 10.1371/journal.pone.0037135
Pubmed ID
Authors

Brant K. Peterson, Jesse N. Weber, Emily H. Kay, Heidi S. Fisher, Hopi E. Hoekstra

Abstract

The ability to efficiently and accurately determine genotypes is a keystone technology in modern genetics, crucial to studies ranging from clinical diagnostics, to genotype-phenotype association, to reconstruction of ancestry and the detection of selection. To date, high capacity, low cost genotyping has been largely achieved via "SNP chip" microarray-based platforms which require substantial prior knowledge of both genome sequence and variability, and once designed are suitable only for those targeted variable nucleotide sites. This method introduces substantial ascertainment bias and inherently precludes detection of rare or population-specific variants, a major source of information for both population history and genotype-phenotype association. Recent developments in reduced-representation genome sequencing experiments on massively parallel sequencers (commonly referred to as RAD-tag or RADseq) have brought direct sequencing to the problem of population genotyping, but increased cost and procedural and analytical complexity have limited their widespread adoption. Here, we describe a complete laboratory protocol, including a custom combinatorial indexing method, and accompanying software tools to facilitate genotyping across large numbers (hundreds or more) of individuals for a range of markers (hundreds to hundreds of thousands). Our method requires no prior genomic knowledge and achieves per-site and per-individual costs below that of current SNP chip technology, while requiring similar hands-on time investment, comparable amounts of input DNA, and downstream analysis times on the order of hours. Finally, we provide empirical results from the application of this method to both genotyping in a laboratory cross and in wild populations. Because of its flexibility, this modified RADseq approach promises to be applicable to a diversity of biological questions in a wide range of organisms.

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Geographical breakdown

Country Count As %
United States 54 1%
Brazil 16 <1%
Canada 10 <1%
United Kingdom 9 <1%
Germany 8 <1%
Spain 7 <1%
France 7 <1%
Switzerland 6 <1%
Portugal 6 <1%
Other 53 1%
Unknown 3708 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 985 25%
Researcher 692 18%
Student > Master 592 15%
Student > Bachelor 345 9%
Student > Doctoral Student 225 6%
Other 506 13%
Unknown 539 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 2220 57%
Biochemistry, Genetics and Molecular Biology 594 15%
Environmental Science 224 6%
Earth and Planetary Sciences 31 <1%
Medicine and Dentistry 28 <1%
Other 151 4%
Unknown 636 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 50. 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 29 April 2023.
All research outputs
#853,406
of 26,017,215 outputs
Outputs from PLOS ONE
#11,182
of 225,486 outputs
Outputs of similar age
#4,317
of 182,669 outputs
Outputs of similar age from PLOS ONE
#144
of 3,786 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 225,486 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.8. This one has done particularly well, scoring higher than 94% 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 182,669 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 96% of its contemporaries.
We're also able to compare this research output to 3,786 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 96% of its contemporaries.