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Controlling for conservation in genome-wide DNA methylation studies

Overview of attention for article published in BMC Genomics, May 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)

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1 blog
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33 tweeters
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Citations

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69 Mendeley
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Title
Controlling for conservation in genome-wide DNA methylation studies
Published in
BMC Genomics, May 2015
DOI 10.1186/s12864-015-1604-3
Pubmed ID
Authors

Meromit Singer, Lior Pachter

Abstract

A commonplace analysis in high-throughput DNA methylation studies is the comparison of methylation extent between different functional regions, computed by averaging methylation states within region types and then comparing averages between regions. For example, it has been reported that methylation is more prevalent in coding regions as compared to their neighboring introns or UTRs, leading to hypotheses about novel forms of epigenetic regulation. We have identified and characterized a bias present in these seemingly straightforward comparisons that results in the false detection of differences in methylation intensities across region types. This bias arises due to differences in conservation rates, rather than methylation rates, and is broadly present in the published literature. When controlling for conservation at coding start sites the differences in DNA methylation rates disappear. Moreover, a re-evaluation of methylation rates at intronexon junctions reveals that the magnitude of previously reported differences is greatly exaggerated. We introduce two correction methods to address this bias, an inferencebased matrix completion algorithm and an averaging approach, tailored to address different underlying biological questions. We evaluate how analysis using these corrections affects the detection of differences in DNA methylation across functional boundaries. We report here on a bias in DNA methylation comparative studies that originates in conservation rate differences and manifests itself in the false discovery of differences in DNA methylation intensities and their extents. We have characterized this bias and its broad implications, and show how to control for it so as to enable the study of a variety of biological questions.

Twitter Demographics

The data shown below were collected from the profiles of 33 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 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 6%
United Kingdom 2 3%
Sweden 1 1%
Ireland 1 1%
Germany 1 1%
Poland 1 1%
Unknown 59 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 36%
Researcher 22 32%
Student > Master 5 7%
Student > Bachelor 3 4%
Student > Doctoral Student 2 3%
Other 8 12%
Unknown 4 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 36 52%
Biochemistry, Genetics and Molecular Biology 14 20%
Computer Science 5 7%
Psychology 2 3%
Immunology and Microbiology 1 1%
Other 4 6%
Unknown 7 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 25. 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 18 October 2018.
All research outputs
#993,445
of 17,829,175 outputs
Outputs from BMC Genomics
#221
of 9,430 outputs
Outputs of similar age
#16,431
of 242,811 outputs
Outputs of similar age from BMC Genomics
#1
of 1 outputs
Altmetric has tracked 17,829,175 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 9,430 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done particularly well, scoring higher than 97% 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 242,811 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 93% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them