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Attention Score in Context
| Title |
A comparison of principal component regression and genomic REML for genomic prediction across populations
|
|---|---|
| Published in |
Genetics Selection Evolution, November 2014
|
| DOI | 10.1186/s12711-014-0060-x |
| Pubmed ID | |
| Authors |
Christos Dadousis, Roel F Veerkamp, Bjørg Heringstad, Marcin Pszczola, Mario PL Calus |
| Abstract |
Genomic prediction faces two main statistical problems: multicollinearity and n ≪ p (many fewer observations than predictor variables). Principal component (PC) analysis is a multivariate statistical method that is often used to address these problems. The objective of this study was to compare the performance of PC regression (PCR) for genomic prediction with that of a commonly used REML model with a genomic relationship matrix (GREML) and to investigate the full potential of PCR for genomic prediction. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Poland | 1 | 2% |
| Unknown | 48 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 27% |
| Student > Master | 10 | 20% |
| Researcher | 8 | 16% |
| Student > Doctoral Student | 4 | 8% |
| Student > Postgraduate | 3 | 6% |
| Other | 5 | 10% |
| Unknown | 6 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 30 | 61% |
| Biochemistry, Genetics and Molecular Biology | 3 | 6% |
| Mathematics | 2 | 4% |
| Veterinary Science and Veterinary Medicine | 2 | 4% |
| Business, Management and Accounting | 1 | 2% |
| Other | 4 | 8% |
| Unknown | 7 | 14% |
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 06 November 2014.
All research outputs
#22,758,309
of 25,373,627 outputs
Outputs from Genetics Selection Evolution
#773
of 822 outputs
Outputs of similar age
#235,608
of 276,333 outputs
Outputs of similar age from Genetics Selection Evolution
#15
of 16 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 276,333 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 16 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.