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Estimation of pleiotropy between complex diseases using single-nucleotide polymorphism-derived genomic relationships and restricted maximum likelihood

Overview of attention for article published in Bioinformatics, July 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

blogs
1 blog
q&a
1 Q&A thread

Citations

dimensions_citation
256 Dimensions

Readers on

mendeley
294 Mendeley
citeulike
1 CiteULike
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Title
Estimation of pleiotropy between complex diseases using single-nucleotide polymorphism-derived genomic relationships and restricted maximum likelihood
Published in
Bioinformatics, July 2012
DOI 10.1093/bioinformatics/bts474
Pubmed ID
Authors

S.H. Lee, J. Yang, M.E. Goddard, P.M. Visscher, N.R. Wray

Abstract

Genetic correlations are the genome-wide aggregate effects of causal variants affecting multiple traits. Traditionally, genetic correlations between complex traits are estimated from pedigree studies, but such estimates can be confounded by shared environmental factors. Moreover, for diseases, low prevalence rates imply that even if the true genetic correlation between disorders was high, co-aggregation of disorders in families might not occur or could not be distinguished from chance. We have developed and implemented statistical methods based on linear mixed models to obtain unbiased estimates of the genetic correlation between pairs of quantitative traits or pairs of binary traits of complex diseases using population-based case-control studies with genome-wide single-nucleotide polymorphism data. The method is validated in a simulation study and applied to estimate genetic correlation between various diseases from Wellcome Trust Case Control Consortium data in a series of bivariate analyses. We estimate a significant positive genetic correlation between risk of Type 2 diabetes and hypertension of ~0.31 (SE 0.14, P = 0.024).

Mendeley readers

The data shown below were compiled from readership statistics for 294 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 2%
United Kingdom 5 2%
Australia 2 <1%
Belgium 1 <1%
Sweden 1 <1%
Netherlands 1 <1%
Canada 1 <1%
Greece 1 <1%
Unknown 275 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 93 32%
Researcher 73 25%
Student > Master 29 10%
Student > Bachelor 20 7%
Professor 18 6%
Other 61 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 114 39%
Biochemistry, Genetics and Molecular Biology 43 15%
Medicine and Dentistry 35 12%
Unspecified 25 9%
Psychology 20 7%
Other 57 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 15 September 2015.
All research outputs
#497,782
of 6,410,771 outputs
Outputs from Bioinformatics
#858
of 5,011 outputs
Outputs of similar age
#11,507
of 108,431 outputs
Outputs of similar age from Bioinformatics
#4
of 34 outputs
Altmetric has tracked 6,410,771 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,011 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.6. This one has done well, scoring higher than 82% 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 108,431 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.