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Genotyping Informatics and Quality Control 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 (95th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

news
3 news outlets
blogs
2 blogs
twitter
8 X users
wikipedia
1 Wikipedia page

Citations

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181 Dimensions

Readers on

mendeley
97 Mendeley
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Title
Genotyping Informatics and Quality Control 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.115.178905
Pubmed ID
Authors

Mark N Kvale, Stephanie Hesselson, Thomas J Hoffmann, Yang Cao, David Chan, Sheryl Connell, Lisa A Croen, Brad P Dispensa, Jasmin Eshragh, Andrea Finn, Jeremy Gollub, Carlos Iribarren, Eric Jorgenson, Lawrence H Kushi, Richard Lao, Yontao Lu, Dana Ludwig, Gurpreet K Mathauda, William B McGuire, Gangwu Mei, Sunita Miles, Michael Mittman, Mohini Patil, Charles P Quesenberry, Dilrini Ranatunga, Sarah Rowell, Marianne Sadler, Lori C Sakoda, Michael Shapero, Ling Shen, Tanu Shenoy, David Smethurst, Carol P Somkin, Stephen K Van Den Eeden, Lawrence Walter, Eunice Wan, Teresa Webster, Rachel A Whitmer, Simon Wong, Chia Zau, Yiping Zhan, Catherine Schaefer, Pui-Yan Kwok, Neil Risch

Abstract

The Kaiser Permanente (KP) Research Program on Genes, Environment and Health (RPGEH), in collaboration with the University of California, San Francisco, undertook genome-wide genotyping of over 100,000 subjects that constitute the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. The project, which generated over 70 billion genotypes, represents the first large scale use of the Affymetrix Axiom Genotyping Solution. Because genotyping took place over a short 14-month period, creating a near-real time analysis pipeline for experimental assay quality control and final optimized analyses was critical. Because of the multi-ethnic nature of the cohort, four different ethnic-specific arrays were employed to enhance genome-wide coverage. All assays were performed on DNA extracted from saliva samples. To improve sample call rates and significantly increase genotype concordance, we partitioned the cohort into disjoint packages of plates with similar assay contexts. Using strict QC criteria, the overall genotyping success rate was 103,067 out of 109,837 samples assayed (93.8%), with a range of 92.1% to 95.4% for the four different arrays. Similarly, the SNP genotyping success rate ranged from 98.1% to 99.4% across the four arrays, the variation mostly depending on how many SNPs were included as single copy versus double copy on a particular array. The high quality and large scale of genotype data created on this cohort, in conjunction with comprehensive longitudinal data from the KP electronic health records of participants will enable a broad range of highly powered genome-wide association studies on a diversity of traits and conditions.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 97 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 2%
Unknown 95 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 21%
Researcher 20 21%
Student > Bachelor 11 11%
Student > Master 9 9%
Professor 5 5%
Other 16 16%
Unknown 16 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 19 20%
Agricultural and Biological Sciences 16 16%
Medicine and Dentistry 14 14%
Computer Science 5 5%
Psychology 3 3%
Other 13 13%
Unknown 27 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 41. 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 11 January 2024.
All research outputs
#1,013,281
of 25,576,801 outputs
Outputs from Genetics
#222
of 7,416 outputs
Outputs of similar age
#11,913
of 279,108 outputs
Outputs of similar age from Genetics
#8
of 82 outputs
Altmetric has tracked 25,576,801 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 7,416 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.6. This one has done particularly well, scoring higher than 97% 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 279,108 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 95% of its contemporaries.
We're also able to compare this research output to 82 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 91% of its contemporaries.