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Concept and design of a genome-wide association genotyping array tailored for transplantation-specific studies

Overview of attention for article published in Genome Medicine, October 2015
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

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7 news outlets
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24 X users

Citations

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47 Dimensions

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70 Mendeley
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Title
Concept and design of a genome-wide association genotyping array tailored for transplantation-specific studies
Published in
Genome Medicine, October 2015
DOI 10.1186/s13073-015-0211-x
Pubmed ID
Authors

Yun R. Li, Jessica van Setten, Shefali S. Verma, Yontao Lu, Michael V. Holmes, Hui Gao, Monkol Lek, Nikhil Nair, Hareesh Chandrupatla, Baoli Chang, Konrad J. Karczewski, Chanel Wong, Maede Mohebnasab, Eyas Mukhtar, Randy Phillips, Vinicius Tragante, Cuiping Hou, Laura Steel, Takesha Lee, James Garifallou, Toumy Guettouche, Hongzhi Cao, Weihua Guan, Aubree Himes, Jacob van Houten, Andrew Pasquier, Reina Yu, Elena Carrigan, Michael B. Miller, David Schladt, Abdullah Akdere, Ana Gonzalez, Kelsey M. Llyod, Daniel McGinn, Abhinav Gangasani, Zach Michaud, Abigail Colasacco, James Snyder, Kelly Thomas, Tiancheng Wang, Baolin Wu, Alhusain J. Alzahrani, Amein K. Al-Ali, Fahad A. Al-Muhanna, Abdullah M. Al-Rubaish, Samir Al-Mueilo, Dimitri S. Monos, Barbara Murphy, Kim M. Olthoff, Cisca Wijmenga, Teresa Webster, Malek Kamoun, Suganthi Balasubramanian, Matthew B. Lanktree, William S. Oetting, Pablo Garcia-Pavia, Daniel G. MacArthur, Paul I W de Bakker, Hakon Hakonarson, Kelly A. Birdwell, Pamala A. Jacobson, Marylyn D. Ritchie, Folkert W. Asselbergs, Ajay K. Israni, Abraham Shaked, Brendan J. Keating

Abstract

In addition to HLA genetic incompatibility, non-HLA difference between donor and recipients of transplantation leading to allograft rejection are now becoming evident. We aimed to create a unique genome-wide platform to facilitate genomic research studies in transplant-related studies. We designed a genome-wide genotyping tool based on the most recent human genomic reference datasets, and included customization for known and potentially relevant metabolic and pharmacological loci relevant to transplantation. We describe here the design and implementation of a customized genome-wide genotyping array, the 'TxArray', comprising approximately 782,000 markers with tailored content for deeper capture of variants across HLA, KIR, pharmacogenomic, and metabolic loci important in transplantation. To test concordance and genotyping quality, we genotyped 85 HapMap samples on the array, including eight trios. We show low Mendelian error rates and high concordance rates for HapMap samples (average parent-parent-child heritability of 0.997, and concordance of 0.996). We performed genotype imputation across autosomal regions, masking directly genotyped SNPs to assess imputation accuracy and report an accuracy of >0.962 for directly genotyped SNPs. We demonstrate much higher capture of the natural killer cell immunoglobulin-like receptor (KIR) region versus comparable platforms. Overall, we show that the genotyping quality and coverage of the TxArray is very high when compared to reference samples and to other genome-wide genotyping platforms. We have designed a comprehensive genome-wide genotyping tool which enables accurate association testing and imputation of ungenotyped SNPs, facilitating powerful and cost-effective large-scale genotyping of transplant-related studies.

X Demographics

X Demographics

The data shown below were collected from the profiles of 24 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 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Sweden 1 1%
Germany 1 1%
France 1 1%
Unknown 66 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 23%
Student > Master 10 14%
Student > Bachelor 8 11%
Student > Ph. D. Student 7 10%
Other 5 7%
Other 12 17%
Unknown 12 17%
Readers by discipline Count As %
Medicine and Dentistry 17 24%
Agricultural and Biological Sciences 9 13%
Biochemistry, Genetics and Molecular Biology 8 11%
Computer Science 5 7%
Pharmacology, Toxicology and Pharmaceutical Science 4 6%
Other 12 17%
Unknown 15 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 61. 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 November 2016.
All research outputs
#677,473
of 24,792,414 outputs
Outputs from Genome Medicine
#130
of 1,528 outputs
Outputs of similar age
#9,793
of 280,581 outputs
Outputs of similar age from Genome Medicine
#4
of 25 outputs
Altmetric has tracked 24,792,414 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,528 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.1. This one has done particularly well, scoring higher than 91% 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 280,581 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 25 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.