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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 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
1 news outlet
twitter
70 tweeters
facebook
2 Facebook pages
wikipedia
3 Wikipedia pages

Citations

dimensions_citation
74 Dimensions

Readers on

mendeley
195 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.

Twitter Demographics

The data shown below were collected from the profiles of 70 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 195 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 5 3%
Germany 4 2%
United States 3 2%
Hungary 2 1%
Spain 2 1%
Israel 1 <1%
France 1 <1%
Austria 1 <1%
Ireland 1 <1%
Other 5 3%
Unknown 170 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 59 30%
Student > Ph. D. Student 56 29%
Student > Master 14 7%
Other 12 6%
Student > Doctoral Student 11 6%
Other 36 18%
Unknown 7 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 91 47%
Biochemistry, Genetics and Molecular Biology 39 20%
Medicine and Dentistry 19 10%
Computer Science 17 9%
Neuroscience 6 3%
Other 10 5%
Unknown 13 7%

Attention Score in Context

This research output has an Altmetric Attention Score of 49. 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 June 2020.
All research outputs
#444,569
of 15,557,170 outputs
Outputs from Bioinformatics
#106
of 9,876 outputs
Outputs of similar age
#4,402
of 157,328 outputs
Outputs of similar age from Bioinformatics
#3
of 182 outputs
Altmetric has tracked 15,557,170 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,876 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one has done particularly well, scoring higher than 98% 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 157,328 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 97% of its contemporaries.
We're also able to compare this research output to 182 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 98% of its contemporaries.