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Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits

Overview of attention for article published in Nature Genetics, March 2012
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

Mentioned by

blogs
2 blogs
twitter
11 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
382 Dimensions

Readers on

mendeley
630 Mendeley
citeulike
8 CiteULike
Title
Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits
Published in
Nature Genetics, March 2012
DOI 10.1038/ng.2213
Pubmed ID
Authors

Jian Yang, Teresa Ferreira, Andrew P Morris, Sarah E Medland, Pamela A F Madden, Andrew C Heath, Nicholas G Martin, Grant W Montgomery, Michael N Weedon, Ruth J Loos, Timothy M Frayling, Mark I McCarthy, Joel N Hirschhorn, Michael E Goddard, Peter M Visscher

Abstract

We present an approximate conditional and joint association analysis that can use summary-level statistics from a meta-analysis of genome-wide association studies (GWAS) and estimated linkage disequilibrium (LD) from a reference sample with individual-level genotype data. Using this method, we analyzed meta-analysis summary data from the GIANT Consortium for height and body mass index (BMI), with the LD structure estimated from genotype data in two independent cohorts. We identified 36 loci with multiple associated variants for height (38 leading and 49 additional SNPs, 87 in total) via a genome-wide SNP selection procedure. The 49 new SNPs explain approximately 1.3% of variance, nearly doubling the heritability explained at the 36 loci. We did not find any locus showing multiple associated SNPs for BMI. The method we present is computationally fast and is also applicable to case-control data, which we demonstrate in an example from meta-analysis of type 2 diabetes by the DIAGRAM Consortium.

Twitter Demographics

The data shown below were collected from the profiles of 11 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 630 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 18 3%
Germany 6 <1%
United Kingdom 5 <1%
Australia 3 <1%
Netherlands 3 <1%
Canada 2 <1%
Denmark 2 <1%
Ireland 2 <1%
Belgium 1 <1%
Other 10 2%
Unknown 578 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 191 30%
Student > Ph. D. Student 188 30%
Student > Master 59 9%
Professor > Associate Professor 34 5%
Student > Bachelor 31 5%
Other 127 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 280 44%
Biochemistry, Genetics and Molecular Biology 108 17%
Medicine and Dentistry 85 13%
Unspecified 47 7%
Computer Science 29 5%
Other 81 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 04 October 2015.
All research outputs
#590,379
of 12,077,615 outputs
Outputs from Nature Genetics
#1,329
of 5,955 outputs
Outputs of similar age
#4,737
of 109,344 outputs
Outputs of similar age from Nature Genetics
#19
of 75 outputs
Altmetric has tracked 12,077,615 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,955 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 28.9. This one has done well, scoring higher than 77% 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 109,344 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 75 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.