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qKAT: a high-throughput qPCR method for KIR gene copy number and haplotype determination

Overview of attention for article published in Genome Medicine, September 2016
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Title
qKAT: a high-throughput qPCR method for KIR gene copy number and haplotype determination
Published in
Genome Medicine, September 2016
DOI 10.1186/s13073-016-0358-0
Pubmed ID
Authors

W. Jiang, C. Johnson, N. Simecek, M. R. López-Álvarez, D. Di, J. Trowsdale, J. A. Traherne

Abstract

Killer cell immunoglobulin-like receptors (KIRs), expressed on natural killer cells and T cells, have considerable biomedical relevance playing significant roles in immunity, pregnancy and transplantation. The KIR locus is one of the most complex and polymorphic regions of the human genome. Extensive sequence homology and copy number variation makes KIRs technically laborious and expensive to type. To aid the investigation of KIRs in human disease we developed a high-throughput, multiplex real-time polymerase chain reaction method to determine gene copy number for each KIR locus. We used reference DNA samples to validate the accuracy and a cohort of 1698 individuals to evaluate capability for precise copy number discrimination. The method provides improved information and identifies KIR haplotype alterations that were not previously visible using other approaches.

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X Demographics

The data shown below were collected from the profile of 1 X user 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 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
United States 1 3%
Unknown 31 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 24%
Student > Master 7 21%
Student > Ph. D. Student 7 21%
Student > Bachelor 4 12%
Student > Doctoral Student 3 9%
Other 1 3%
Unknown 3 9%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 27%
Agricultural and Biological Sciences 7 21%
Medicine and Dentistry 5 15%
Immunology and Microbiology 3 9%
Engineering 2 6%
Other 2 6%
Unknown 5 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 30 September 2016.
All research outputs
#18,473,108
of 22,890,496 outputs
Outputs from Genome Medicine
#1,372
of 1,443 outputs
Outputs of similar age
#284,592
of 393,722 outputs
Outputs of similar age from Genome Medicine
#44
of 47 outputs
Altmetric has tracked 22,890,496 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
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We're also able to compare this research output to 47 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.