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Successful use of whole genome amplified DNA from multiple source types for high-density Illumina SNP microarrays

Overview of attention for article published in BMC Genomics, March 2018
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Title
Successful use of whole genome amplified DNA from multiple source types for high-density Illumina SNP microarrays
Published in
BMC Genomics, March 2018
DOI 10.1186/s12864-018-4572-6
Pubmed ID
Authors

Casey L. Dagnall, Lindsay M. Morton, Belynda D. Hicks, Shengchao Li, Weiyin Zhou, Eric Karlins, Kedest Teshome, Salma Chowdhury, Kerrie S. Lashley, Joshua N. Sampson, Leslie L. Robison, Gregory T. Armstrong, Smita Bhatia, Gretchen A. Radloff, Stella M. Davies, Margaret A. Tucker, Meredith Yeager, Stephen J. Chanock

Abstract

The recommended genomic DNA input requirements for whole genome single nucleotide polymorphism microarrays can limit the scope of molecular epidemiological studies. We performed a large-scale evaluation of whole genome amplified DNA as input into high-density, whole-genome Illumina® Infinium® SNP microarray. Overall, 6622 DNA samples from 5970 individuals were obtained from three distinct biospecimen sources and genotyped using gDNA and/or wgaDNA inputs. When genotypes from the same individual were compared with standard, native gDNA input amount, we observed 99.94% mean concordance with wgaDNA input. Our results demonstrate that carefully conducted studies with wgaDNA inputs can yield high-quality genotyping results. These findings should enable investigators to consider expansion of ongoing studies using high-density SNP microarrays, currently challenged by small amounts of available DNA.

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The data shown below were collected from the profiles of 2 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 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 11%
Other 3 11%
Researcher 3 11%
Student > Ph. D. Student 3 11%
Professor 2 7%
Other 5 18%
Unknown 9 32%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 39%
Agricultural and Biological Sciences 4 14%
Medicine and Dentistry 3 11%
Sports and Recreations 1 4%
Energy 1 4%
Other 1 4%
Unknown 7 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 13 March 2018.
All research outputs
#14,264,158
of 23,305,591 outputs
Outputs from BMC Genomics
#5,402
of 10,742 outputs
Outputs of similar age
#183,080
of 332,674 outputs
Outputs of similar age from BMC Genomics
#90
of 177 outputs
Altmetric has tracked 23,305,591 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,742 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 46th percentile – i.e., 46% of its peers scored the same or lower than it.
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 332,674 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 177 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.