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Estimating directional epistasis

Overview of attention for article published in Frontiers in Genetics, July 2014
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Title
Estimating directional epistasis
Published in
Frontiers in Genetics, July 2014
DOI 10.3389/fgene.2014.00198
Pubmed ID
Authors

Arnaud Le Rouzic

Abstract

Epistasis, i.e., the fact that gene effects depend on the genetic background, is a direct consequence of the complexity of genetic architectures. Despite this, most of the models used in evolutionary and quantitative genetics pay scant attention to genetic interactions. For instance, the traditional decomposition of genetic effects models epistasis as noise around the evolutionarily-relevant additive effects. Such an approach is only valid if it is assumed that there is no general pattern among interactions-a highly speculative scenario. Systematic interactions generate directional epistasis, which has major evolutionary consequences. In spite of its importance, directional epistasis is rarely measured or reported by quantitative geneticists, not only because its relevance is generally ignored, but also due to the lack of simple, operational, and accessible methods for its estimation. This paper describes conceptual and statistical tools that can be used to estimate directional epistasis from various kinds of data, including QTL mapping results, phenotype measurements in mutants, and artificial selection responses. As an illustration, I measured directional epistasis from a real-life example. I then discuss the interpretation of the estimates, showing how they can be used to draw meaningful biological inferences.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Poland 1 3%
Germany 1 3%
France 1 3%
Unknown 35 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 29%
Student > Ph. D. Student 9 24%
Student > Master 5 13%
Student > Doctoral Student 2 5%
Professor 1 3%
Other 3 8%
Unknown 7 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 34%
Biochemistry, Genetics and Molecular Biology 12 32%
Environmental Science 2 5%
Computer Science 2 5%
Chemistry 1 3%
Other 0 0%
Unknown 8 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 11 August 2014.
All research outputs
#14,083,834
of 24,552,012 outputs
Outputs from Frontiers in Genetics
#3,014
of 13,233 outputs
Outputs of similar age
#108,482
of 231,932 outputs
Outputs of similar age from Frontiers in Genetics
#68
of 133 outputs
Altmetric has tracked 24,552,012 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,233 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done well, scoring higher than 76% 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 231,932 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 52% of its contemporaries.
We're also able to compare this research output to 133 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.