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Non-Synonymous and Synonymous Coding SNPs Show Similar Likelihood and Effect Size of Human Disease Association

Overview of attention for article published in PLOS ONE, October 2010
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

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6 X users
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1 Q&A thread

Citations

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158 Dimensions

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269 Mendeley
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16 CiteULike
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Title
Non-Synonymous and Synonymous Coding SNPs Show Similar Likelihood and Effect Size of Human Disease Association
Published in
PLOS ONE, October 2010
DOI 10.1371/journal.pone.0013574
Pubmed ID
Authors

Rong Chen, Eugene V. Davydov, Marina Sirota, Atul J. Butte

Abstract

Many DNA variants have been identified on more than 300 diseases and traits using Genome-Wide Association Studies (GWASs). Some have been validated using deep sequencing, but many fewer have been validated functionally, primarily focused on non-synonymous coding SNPs (nsSNPs). It is an open question whether synonymous coding SNPs (sSNPs) and other non-coding SNPs can lead to as high odds ratios as nsSNPs. We conducted a broad survey across 21,429 disease-SNP associations curated from 2,113 publications studying human genetic association, and found that nsSNPs and sSNPs shared similar likelihood and effect size for disease association. The enrichment of disease-associated SNPs around the 80(th) base in the first introns might provide an effective way to prioritize intronic SNPs for functional studies. We further found that the likelihood of disease association was positively associated with the effect size across different types of SNPs, and SNPs in the 3' untranslated regions, such as the microRNA binding sites, might be under-investigated. Our results suggest that sSNPs are just as likely to be involved in disease mechanisms, so we recommend that sSNPs discovered from GWAS should also be examined with functional studies.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 269 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 10 4%
United Kingdom 3 1%
Mexico 2 <1%
Belgium 2 <1%
Spain 2 <1%
Hong Kong 1 <1%
Russia 1 <1%
Germany 1 <1%
Japan 1 <1%
Other 1 <1%
Unknown 245 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 67 25%
Student > Ph. D. Student 61 23%
Professor > Associate Professor 21 8%
Student > Bachelor 21 8%
Other 18 7%
Other 47 17%
Unknown 34 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 133 49%
Biochemistry, Genetics and Molecular Biology 45 17%
Medicine and Dentistry 20 7%
Computer Science 9 3%
Immunology and Microbiology 5 2%
Other 20 7%
Unknown 37 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 21 September 2014.
All research outputs
#5,463,628
of 22,649,029 outputs
Outputs from PLOS ONE
#66,176
of 193,361 outputs
Outputs of similar age
#27,102
of 99,462 outputs
Outputs of similar age from PLOS ONE
#426
of 933 outputs
Altmetric has tracked 22,649,029 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 193,361 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. 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 99,462 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 72% of its contemporaries.
We're also able to compare this research output to 933 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 54% of its contemporaries.