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Utilizing Ethnic-Specific Differences in Minor Allele Frequency to Recategorize Reported Pathogenic Deafness Variants

Overview of attention for article published in American Journal of Human Genetics, September 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 (90th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (51st percentile)

Mentioned by

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12 X users
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2 patents
wikipedia
1 Wikipedia page

Readers on

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151 Mendeley
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2 CiteULike
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Article details
Title
Utilizing Ethnic-Specific Differences in Minor Allele Frequency to Recategorize Reported Pathogenic Deafness Variants
Published in
American Journal of Human Genetics, September 2014
DOI 10.1016/j.ajhg.2014.09.001
Pubmed ID
Authors
Abstract

Ethnic-specific differences in minor allele frequency impact variant categorization for genetic screening of nonsyndromic hearing loss (NSHL) and other genetic disorders. We sought to evaluate all previously reported pathogenic NSHL variants in the context of a large number of controls from ethnically distinct populations sequenced with orthogonal massively parallel sequencing methods. We used HGMD, ClinVar, and dbSNP to generate a comprehensive list of reported pathogenic NSHL variants and re-evaluated these variants in the context of 8,595 individuals from 12 populations and 6 ethnically distinct major human evolutionary phylogenetic groups from three sources (Exome Variant Server, 1000 Genomes project, and a control set of individuals created for this study, the OtoDB). Of the 2,197 reported pathogenic deafness variants, 325 (14.8%) were present in at least one of the 8,595 controls, indicating a minor allele frequency (MAF) > 0.00006. MAFs ranged as high as 0.72, a level incompatible with pathogenicity for a fully penetrant disease like NSHL. Based on these data, we established MAF thresholds of 0.005 for autosomal-recessive variants (excluding specific variants in GJB2) and 0.0005 for autosomal-dominant variants. Using these thresholds, we recategorized 93 (4.2%) of reported pathogenic variants as benign. Our data show that evaluation of reported pathogenic deafness variants using variant MAFs from multiple distinct ethnicities and sequenced by orthogonal methods provides a powerful filter for determining pathogenicity. The proposed MAF thresholds will facilitate clinical interpretation of variants identified in genetic testing for NSHL. All data are publicly available to facilitate interpretation of genetic variants causing deafness.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 151 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 2 1%
Israel 1 <1%
Unknown 148 98%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 26 17%
Student > Master 22 15%
Student > Ph. D. Student 21 14%
Other 16 11%
Student > Postgraduate 10 7%
Other 26 17%
Unknown 30 20%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 37 25%
Biochemistry, Genetics and Molecular Biology 33 22%
Medicine and Dentistry 32 21%
Arts and Humanities 2 1%
Computer Science 2 1%
Other 7 5%
Unknown 38 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 23 November 2022.
All research outputs
#3,196,640
of 34,526,284 outputs
Outputs from American Journal of Human Genetics
#1,694
of 7,836 outputs
Outputs of similar age
#28,917
of 295,956 outputs
Outputs of similar age from American Journal of Human Genetics
#17
of 35 outputs
Altmetric has tracked 34,526,284 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,836 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.6. 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 295,956 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 90% of its contemporaries.
We're also able to compare this research output to 35 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 51% of its contemporaries.