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Gene-specific patterns of expression variation across organs and species

Overview of attention for article published in Genome Biology, July 2016
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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 (91st percentile)
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

Mentioned by

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1 blog
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32 X users

Citations

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83 Dimensions

Readers on

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238 Mendeley
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7 CiteULike
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Title
Gene-specific patterns of expression variation across organs and species
Published in
Genome Biology, July 2016
DOI 10.1186/s13059-016-1008-y
Pubmed ID
Authors

Alessandra Breschi, Sarah Djebali, Jesse Gillis, Dmitri D. Pervouchine, Alex Dobin, Carrie A. Davis, Thomas R. Gingeras, Roderic Guigó

Abstract

A comparison of transcriptional profiles derived from different tissues in a given species or among different species assumes that commonalities reflect evolutionarily conserved programs and that differences reflect species or tissue responses to environmental conditions or developmental program staging. Apparently conflicting results have been published regarding whether organ-specific transcriptional patterns dominate over species-specific patterns, or vice versa, making it unclear to what extent the biology of a given organism can be extrapolated to another. These studies have in common that they treat the transcriptomes monolithically, implicitly ignoring that each gene is likely to have a specific pattern of transcriptional variation across organs and species. We use linear models to quantify this pattern. We find a continuum in the spectrum of expression variation: the expression of some genes varies considerably across species and little across organs, and simply reflects evolutionary distance. At the other extreme are genes whose expression varies considerably across organs and little across species; these genes are much more likely to be associated with diseases than are genes whose expression varies predominantly across species. Whether transcriptomes, when considered globally, cluster preferentially according to one component or the other may not be a property of the transcriptomes, but rather a consequence of the dominant behavior of a subset of genes. Therefore, the values of the components of the variance of expression for each gene could become a useful resource when planning, interpreting, and extrapolating experimental data from mouse to humans.

X Demographics

X Demographics

The data shown below were collected from the profiles of 32 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 238 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 1%
United Kingdom 2 <1%
Spain 2 <1%
Denmark 2 <1%
Chile 1 <1%
Australia 1 <1%
China 1 <1%
Unknown 226 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 59 25%
Student > Ph. D. Student 56 24%
Student > Master 23 10%
Student > Bachelor 15 6%
Professor > Associate Professor 11 5%
Other 36 15%
Unknown 38 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 99 42%
Biochemistry, Genetics and Molecular Biology 60 25%
Computer Science 9 4%
Medicine and Dentistry 6 3%
Neuroscience 5 2%
Other 13 5%
Unknown 46 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 01 August 2016.
All research outputs
#1,686,376
of 25,373,627 outputs
Outputs from Genome Biology
#1,374
of 4,467 outputs
Outputs of similar age
#30,607
of 370,765 outputs
Outputs of similar age from Genome Biology
#20
of 62 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has gotten more attention than average, scoring higher than 69% 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 370,765 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 91% of its contemporaries.
We're also able to compare this research output to 62 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 67% of its contemporaries.