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Attention Score in Context
| Title |
Compatibility of pedigree-based and marker-based relationship matrices for single-step genetic evaluation
|
|---|---|
| Published in |
Genetics Selection Evolution, December 2012
|
| DOI | 10.1186/1297-9686-44-37 |
| Pubmed ID | |
| Authors |
Ole F Christensen |
| Abstract |
Single-step methods provide a coherent and conceptually simple approach to incorporate genomic information into genetic evaluations. An issue with single-step methods is compatibility between the marker-based relationship matrix for genotyped animals and the pedigree-based relationship matrix. Therefore, it is necessary to adjust the marker-based relationship matrix to the pedigree-based relationship matrix. Moreover, with data from routine evaluations, this adjustment should in principle be based on both observed marker genotypes and observed phenotypes, but until now this has been overlooked. In this paper, I propose a new method to address this issue by 1) adjusting the pedigree-based relationship matrix to be compatible with the marker-based relationship matrix instead of the reverse and 2) extending the single-step genetic evaluation using a joint likelihood of observed phenotypes and observed marker genotypes. The performance of this method is then evaluated using two simulated datasets. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 1% |
| France | 1 | 1% |
| Argentina | 1 | 1% |
| Brazil | 1 | 1% |
| Unknown | 77 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 20 | 25% |
| Student > Ph. D. Student | 19 | 23% |
| Student > Master | 10 | 12% |
| Student > Doctoral Student | 4 | 5% |
| Other | 3 | 4% |
| Other | 9 | 11% |
| Unknown | 16 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 53 | 65% |
| Biochemistry, Genetics and Molecular Biology | 3 | 4% |
| Medicine and Dentistry | 2 | 2% |
| Mathematics | 2 | 2% |
| Veterinary Science and Veterinary Medicine | 1 | 1% |
| Other | 2 | 2% |
| Unknown | 18 | 22% |
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 30 December 2015.
All research outputs
#17,285,668
of 25,373,627 outputs
Outputs from Genetics Selection Evolution
#550
of 822 outputs
Outputs of similar age
#191,702
of 286,152 outputs
Outputs of similar age from Genetics Selection Evolution
#5
of 7 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 822 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
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We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.