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Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel

Overview of attention for article published in Nature Communications, September 2015
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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 (96th percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

Mentioned by

news
3 news outlets
blogs
3 blogs
twitter
42 X users
facebook
1 Facebook page

Citations

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310 Dimensions

Readers on

mendeley
361 Mendeley
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4 CiteULike
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Title
Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel
Published in
Nature Communications, September 2015
DOI 10.1038/ncomms9111
Pubmed ID
Authors

Jie Huang, Bryan Howie, Shane McCarthy, Yasin Memari, Klaudia Walter, Josine L. Min, Petr Danecek, Giovanni Malerba, Elisabetta Trabetti, Hou-Feng Zheng, Giovanni Gambaro, J. Brent Richards, Richard Durbin, Nicholas J. Timpson, Jonathan Marchini, Nicole Soranzo

Abstract

Imputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced at low depth (average 7x), aiming to exhaustively characterize genetic variation down to 0.1% minor allele frequency in the British population. Here we demonstrate the value of this resource for improving imputation accuracy at rare and low-frequency variants in both a UK and an Italian population. We show that large increases in imputation accuracy can be achieved by re-phasing WGS reference panels after initial genotype calling. We also present a method for combining WGS panels to improve variant coverage and downstream imputation accuracy, which we illustrate by integrating 7,562 WGS haplotypes from the UK10K project with 2,184 haplotypes from the 1000 Genomes Project. Finally, we introduce a novel approximation that maintains speed without sacrificing imputation accuracy for rare variants.

X Demographics

X Demographics

The data shown below were collected from the profiles of 42 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 361 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 4 1%
Italy 2 <1%
United States 2 <1%
Netherlands 1 <1%
Australia 1 <1%
South Africa 1 <1%
Finland 1 <1%
France 1 <1%
Canada 1 <1%
Other 3 <1%
Unknown 344 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 95 26%
Student > Ph. D. Student 83 23%
Student > Master 25 7%
Professor 20 6%
Other 15 4%
Other 49 14%
Unknown 74 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 89 25%
Agricultural and Biological Sciences 79 22%
Medicine and Dentistry 52 14%
Engineering 8 2%
Computer Science 7 2%
Other 29 8%
Unknown 97 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 59. 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 July 2023.
All research outputs
#735,316
of 25,837,817 outputs
Outputs from Nature Communications
#12,567
of 58,118 outputs
Outputs of similar age
#10,036
of 282,563 outputs
Outputs of similar age from Nature Communications
#195
of 768 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 58,118 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 55.5. This one has done well, scoring higher than 78% 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 282,563 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 96% of its contemporaries.
We're also able to compare this research output to 768 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.