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Attention Score in Context
| Title |
Genomic selection using low density marker panels with application to a sire line in pigs
|
|---|---|
| Published in |
Genetics Selection Evolution, July 2013
|
| DOI | 10.1186/1297-9686-45-28 |
| Pubmed ID | |
| Authors |
Robin Wellmann, Siegfried Preuß, Ernst Tholen, Jörg Heinkel, Klaus Wimmers, Jörn Bennewitz |
| Abstract |
Genomic selection has become a standard tool in dairy cattle breeding. However, for other animal species, implementation of this technology is hindered by the high cost of genotyping. One way to reduce the routine costs is to genotype selection candidates with an SNP (single nucleotide polymorphism) panel of reduced density. This strategy is investigated in the present paper. Methods are proposed for the approximation of SNP positions, for selection of SNPs to be included in the low-density panel, for genotype imputation, and for the estimation of the accuracy of genomic breeding values. The imputation method was developed for a situation in which selection candidates are genotyped with an SNP panel of reduced density but have high-density genotyped sires. The dams of selection candidates are not genotyped. The methods were applied to a sire line pig population with 895 German Piétrain boars genotyped with the PorcineSNP60 BeadChip. |
Mendeley readers
The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 4% |
| Denmark | 1 | 1% |
| France | 1 | 1% |
| Brazil | 1 | 1% |
| Unknown | 77 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 24 | 29% |
| Researcher | 16 | 19% |
| Student > Master | 11 | 13% |
| Other | 6 | 7% |
| Student > Doctoral Student | 4 | 5% |
| Other | 10 | 12% |
| Unknown | 12 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 51 | 61% |
| Biochemistry, Genetics and Molecular Biology | 6 | 7% |
| Computer Science | 3 | 4% |
| Veterinary Science and Veterinary Medicine | 2 | 2% |
| Medicine and Dentistry | 2 | 2% |
| Other | 4 | 5% |
| Unknown | 15 | 18% |
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 11 January 2014.
All research outputs
#22,759,452
of 25,373,627 outputs
Outputs from Genetics Selection Evolution
#773
of 822 outputs
Outputs of similar age
#187,072
of 209,988 outputs
Outputs of similar age from Genetics Selection Evolution
#11
of 11 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% 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 1st percentile – i.e., 1% 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 209,988 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.