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voom: precision weights unlock linear model analysis tools for RNA-seq read counts

Overview of attention for article published in Genome Biology, February 2014
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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 (98th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Citations

dimensions_citation
4721 Dimensions

Readers on

mendeley
3313 Mendeley
citeulike
17 CiteULike
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Title
voom: precision weights unlock linear model analysis tools for RNA-seq read counts
Published in
Genome Biology, February 2014
DOI 10.1186/gb-2014-15-2-r29
Pubmed ID
Authors

Charity W Law, Yunshun Chen, Wei Shi, Gordon K Smyth

X Demographics

X Demographics

The data shown below were collected from the profiles of 59 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 3,313 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 37 1%
United Kingdom 12 <1%
Australia 7 <1%
Germany 7 <1%
Netherlands 6 <1%
Spain 5 <1%
China 4 <1%
Brazil 4 <1%
Denmark 3 <1%
Other 23 <1%
Unknown 3205 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 851 26%
Researcher 665 20%
Student > Master 356 11%
Student > Bachelor 260 8%
Student > Doctoral Student 168 5%
Other 430 13%
Unknown 583 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 1002 30%
Biochemistry, Genetics and Molecular Biology 817 25%
Medicine and Dentistry 175 5%
Computer Science 152 5%
Immunology and Microbiology 88 3%
Other 395 12%
Unknown 684 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 90. 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 26 March 2024.
All research outputs
#481,049
of 25,837,817 outputs
Outputs from Genome Biology
#265
of 4,513 outputs
Outputs of similar age
#4,658
of 326,118 outputs
Outputs of similar age from Genome Biology
#8
of 102 outputs
Altmetric has tracked 25,837,817 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 4,513 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.7. This one has done particularly well, scoring higher than 93% 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 326,118 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 98% of its contemporaries.
We're also able to compare this research output to 102 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 92% of its contemporaries.