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Comparison of genotyping using pooled DNA samples (allelotyping) and individual genotyping using the affymetrix genome-wide human SNP array 6.0

Overview of attention for article published in BMC Genomics, July 2013
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  • Good Attention Score compared to outputs of the same age and source (65th percentile)

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Title
Comparison of genotyping using pooled DNA samples (allelotyping) and individual genotyping using the affymetrix genome-wide human SNP array 6.0
Published in
BMC Genomics, July 2013
DOI 10.1186/1471-2164-14-506
Pubmed ID
Authors

Alexander Teumer, Florian D Ernst, Anja Wiechert, Katharina Uhr, Matthias Nauck, Astrid Petersmann, Henry Völzke, Uwe Völker, Georg Homuth

Abstract

Genome-wide association studies (GWAS) using array-based genotyping technology are widely used to identify genetic loci associated with complex diseases or other phenotypes. The costs of GWAS projects based on individual genotyping are still comparatively high and increase with the size of study populations. Genotyping using pooled DNA samples, as also being referred as to allelotyping approach, offers an alternative at affordable costs. In the present study, data from 100 DNA samples individually genotyped with the Affymetrix Genome-Wide Human SNP Array 6.0 were used to estimate the error of the pooling approach by comparing the results with those obtained using the same array type but DNA pools each composed of 50 of the same samples. Newly developed and established methods for signal intensity correction were applied. Furthermore, the relative allele intensity signals (RAS) obtained by allelotyping were compared to the corresponding values derived from individual genotyping. Similarly, differences in RAS values between pools were determined and compared.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Netherlands 1 2%
Australia 1 2%
Unknown 39 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 36%
Student > Bachelor 4 10%
Professor 4 10%
Student > Ph. D. Student 4 10%
Student > Master 3 7%
Other 5 12%
Unknown 7 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 45%
Biochemistry, Genetics and Molecular Biology 4 10%
Computer Science 3 7%
Engineering 2 5%
Medicine and Dentistry 2 5%
Other 1 2%
Unknown 11 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 09 November 2016.
All research outputs
#8,261,140
of 25,371,288 outputs
Outputs from BMC Genomics
#3,703
of 11,244 outputs
Outputs of similar age
#68,426
of 209,852 outputs
Outputs of similar age from BMC Genomics
#60
of 175 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 65% 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 209,852 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 175 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 65% of its contemporaries.