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Gene-set analysis is severely biased when applied to genome-wide methylation data

Overview of attention for article published in Bioinformatics, June 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

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56 X users
facebook
2 Facebook pages
wikipedia
4 Wikipedia pages

Citations

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125 Dimensions

Readers on

mendeley
218 Mendeley
citeulike
7 CiteULike
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Title
Gene-set analysis is severely biased when applied to genome-wide methylation data
Published in
Bioinformatics, June 2013
DOI 10.1093/bioinformatics/btt311
Pubmed ID
Authors

Paul Geeleher, Lori Hartnett, Laurance J. Egan, Aaron Golden, Raja Affendi Raja Ali, Cathal Seoighe

Abstract

DNA methylation is an epigenetic mark that can stably repress gene expression. Because of its biological and clinical significance, several methods have been developed to compare genome-wide patterns of methylation between groups of samples. The application of gene set analysis to identify relevant groups of genes that are enriched for differentially methylated genes is often a major component of the analysis of these data. This can be used, for example, to identify processes or pathways that are perturbed in disease development. We show that gene-set analysis, as it is typically applied to genome-wide methylation assays, is severely biased as a result of differences in the numbers of CpG sites associated with different classes of genes and gene promoters.

X Demographics

X Demographics

The data shown below were collected from the profiles of 56 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 218 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 5 2%
Germany 4 2%
United States 3 1%
Hungary 2 <1%
Spain 2 <1%
France 1 <1%
Hong Kong 1 <1%
Austria 1 <1%
Israel 1 <1%
Other 5 2%
Unknown 193 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 63 29%
Student > Ph. D. Student 62 28%
Student > Master 14 6%
Student > Doctoral Student 12 6%
Other 11 5%
Other 41 19%
Unknown 15 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 90 41%
Biochemistry, Genetics and Molecular Biology 42 19%
Medicine and Dentistry 19 9%
Computer Science 19 9%
Neuroscience 6 3%
Other 19 9%
Unknown 23 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 34. 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 30 May 2019.
All research outputs
#1,212,338
of 26,017,215 outputs
Outputs from Bioinformatics
#422
of 12,966 outputs
Outputs of similar age
#9,644
of 212,147 outputs
Outputs of similar age from Bioinformatics
#8
of 215 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,966 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has done particularly well, scoring higher than 96% 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 212,147 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 94% of its contemporaries.
We're also able to compare this research output to 215 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 96% of its contemporaries.