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Saturated linkage map construction in Rubus idaeususing genotyping by sequencing and genome-independent imputation

Overview of attention for article published in BMC Genomics, January 2013
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3 X users

Citations

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160 Dimensions

Readers on

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238 Mendeley
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1 CiteULike
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Title
Saturated linkage map construction in Rubus idaeususing genotyping by sequencing and genome-independent imputation
Published in
BMC Genomics, January 2013
DOI 10.1186/1471-2164-14-2
Pubmed ID
Authors

Judson A Ward, Jasbir Bhangoo, Felicidad Fernández-Fernández, Patrick Moore, JD Swanson, Roberto Viola, Riccardo Velasco, Nahla Bassil, Courtney A Weber, Daniel J Sargent

Abstract

Rapid development of highly saturated genetic maps aids molecular breeding, which can accelerate gain per breeding cycle in woody perennial plants such as Rubus idaeus (red raspberry). Recently, robust genotyping methods based on high-throughput sequencing were developed, which provide high marker density, but result in some genotype errors and a large number of missing genotype values. Imputation can reduce the number of missing values and can correct genotyping errors, but current methods of imputation require a reference genome and thus are not an option for most species.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 238 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 3%
Brazil 3 1%
Italy 2 <1%
Germany 1 <1%
Ireland 1 <1%
Norway 1 <1%
Netherlands 1 <1%
Sweden 1 <1%
France 1 <1%
Other 2 <1%
Unknown 219 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 64 27%
Researcher 59 25%
Student > Master 30 13%
Student > Doctoral Student 15 6%
Student > Postgraduate 11 5%
Other 29 12%
Unknown 30 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 164 69%
Biochemistry, Genetics and Molecular Biology 21 9%
Environmental Science 3 1%
Computer Science 3 1%
Medicine and Dentistry 3 1%
Other 8 3%
Unknown 36 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 23 January 2019.
All research outputs
#16,048,009
of 25,374,917 outputs
Outputs from BMC Genomics
#6,103
of 11,244 outputs
Outputs of similar age
#181,967
of 292,951 outputs
Outputs of similar age from BMC Genomics
#92
of 179 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 41st percentile – i.e., 41% of its peers scored the same or lower than it.
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 292,951 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 179 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.