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Characterizing Race/Ethnicity and Genetic Ancestry for 100,000 Subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort

Overview of attention for article published in Genetics, June 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 (98th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

news
7 news outlets
blogs
2 blogs
twitter
20 tweeters
wikipedia
1 Wikipedia page
googleplus
1 Google+ user

Citations

dimensions_citation
112 Dimensions

Readers on

mendeley
116 Mendeley
citeulike
2 CiteULike
Title
Characterizing Race/Ethnicity and Genetic Ancestry for 100,000 Subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort
Published in
Genetics, June 2015
DOI 10.1534/genetics.115.178616
Pubmed ID
Authors

Yambazi Banda, Mark N. Kvale, Thomas J. Hoffmann, Stephanie E. Hesselson, Dilrini Ranatunga, Hua Tang, Chiara Sabatti, Lisa A. Croen, Brad P. Dispensa, Mary Henderson, Carlos Iribarren, Eric Jorgenson, Lawrence H. Kushi, Dana Ludwig, Diane Olberg, Charles P. Quesenberry, Sarah Rowell, Marianne Sadler, Lori C. Sakoda, Stanley Sciortino, Ling Shen, David Smethurst, Carol P. Somkin, Stephen K. Van Den Eeden, Lawrence Walter, Rachel A. Whitmer, Pui-Yan Kwok, Catherine Schaefer, Neil Risch

Abstract

Using genome-wide genotypes, we characterized the genetic structure of 103,006 participants in the Kaiser Permanente Northern California multi-ethnic Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort and analyzed the relationship to self-reported race/ethnicity. Participants endorsed any of 23 race/ethnicity/nationality categories, which were collapsed into 7 major race/ethnicity groups. By self-report the cohort is 80.8% white and 19.2% minority; 93.8% endorsed a single race/ethnicity group, while 6.2% endorsed two or more. PC and admixture analyses were generally consistent with prior studies. Approximately 17% of subjects had genetic ancestry from more than one continent, and 12% were genetically admixed considering only non-adjacent geographical origins. Self-reported whites were spread on a continuum along the first two PCs, indicating extensive mixing among European nationalities. Self-identified East Asian nationalities correlated with genetic clustering, consistent with extensive endogamy. Individuals of mixed East Asian-European genetic ancestry were easily identified; we also observed a modest amount of European genetic ancestry in individuals self-identified as Filipinos. Self-reported African Americans and Latinos showed extensive European and African genetic ancestry, and Native American genetic ancestry for the latter. Among 3,741 genetically-identified parent-child pairs, 93% were concordant for self-reported race/ethnicity; among 2,018 genetically-identified full-sib pairs, 96% were concordant; the lower rate for parent-child pairs was largely due to inter-marriage. The parent-child pairs revealed a trend towards increasing exogamy over time; the presence in the cohort of individuals endorsing multiple race/ethnicity categories, creates interesting challenges and future opportunities for genetic epidemiologic studies.

Twitter Demographics

The data shown below were collected from the profiles of 20 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
United Kingdom 1 <1%
Brazil 1 <1%
Netherlands 1 <1%
Canada 1 <1%
Unknown 109 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 30 26%
Student > Ph. D. Student 29 25%
Student > Master 13 11%
Student > Bachelor 11 9%
Unspecified 9 8%
Other 24 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 32 28%
Unspecified 24 21%
Biochemistry, Genetics and Molecular Biology 20 17%
Medicine and Dentistry 16 14%
Computer Science 6 5%
Other 18 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 83. 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 18 October 2019.
All research outputs
#209,995
of 13,855,967 outputs
Outputs from Genetics
#60
of 4,784 outputs
Outputs of similar age
#4,016
of 231,906 outputs
Outputs of similar age from Genetics
#5
of 94 outputs
Altmetric has tracked 13,855,967 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,784 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.8. This one has done particularly well, scoring higher than 98% 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 231,906 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 98% of its contemporaries.
We're also able to compare this research output to 94 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.