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Trans-ethnic genome-wide association studies: advantages and challenges of mapping in diverse populations

Overview of attention for article published in Genome Medicine, October 2014
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

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1 news outlet
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10 X users

Citations

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174 Dimensions

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203 Mendeley
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Title
Trans-ethnic genome-wide association studies: advantages and challenges of mapping in diverse populations
Published in
Genome Medicine, October 2014
DOI 10.1186/s13073-014-0091-5
Pubmed ID
Authors

Yun R Li, Brendan J Keating

Abstract

Genome-wide association studies (GWASs) are the method most often used by geneticists to interrogate the human genome, and they provide a cost-effective way to identify the genetic variants underpinning complex traits and diseases. Most initial GWASs have focused on genetically homogeneous cohorts from European populations given the limited availability of ethnic minority samples and so as to limit population stratification effects. Transethnic studies have been invaluable in explaining the heritability of common quantitative traits, such as height, and in examining the genetic architecture of complex diseases, such as type 2 diabetes. They provide an opportunity for large-scale signal replication in independent populations and for cross-population meta-analyses to boost statistical power. In addition, transethnic GWASs enable prioritization of candidate genes, fine-mapping of functional variants, and potentially identification of SNPs associated with disease risk in admixed populations, by taking advantage of natural differences in genomic linkage disequilibrium across ethnically diverse populations. Recent efforts to assess the biological function of variants identified by GWAS have highlighted the need for large-scale replication, meta-analyses and fine-mapping across worldwide populations of ethnically diverse genetic ancestries. Here, we review recent advances and new approaches that are important to consider when performing, designing or interpreting transethnic GWASs, and we highlight existing challenges, such as the limited ability to handle heterogeneity in linkage disequilibrium across populations and limitations in dissecting complex architectures, such as those found in recently admixed populations.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 203 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 <1%
United Kingdom 1 <1%
Nigeria 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 198 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 53 26%
Researcher 33 16%
Student > Master 25 12%
Student > Bachelor 25 12%
Student > Doctoral Student 11 5%
Other 27 13%
Unknown 29 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 56 28%
Agricultural and Biological Sciences 43 21%
Medicine and Dentistry 26 13%
Psychology 6 3%
Mathematics 6 3%
Other 24 12%
Unknown 42 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 31 October 2020.
All research outputs
#2,871,701
of 22,769,322 outputs
Outputs from Genome Medicine
#649
of 1,437 outputs
Outputs of similar age
#35,205
of 260,444 outputs
Outputs of similar age from Genome Medicine
#25
of 57 outputs
Altmetric has tracked 22,769,322 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,437 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.7. This one has gotten more attention than average, scoring higher than 54% 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 260,444 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 86% of its contemporaries.
We're also able to compare this research output to 57 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 56% of its contemporaries.