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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 (Online Edition), January 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 (90th percentile)

Citations

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3877 Dimensions

Readers on

mendeley
3012 Mendeley
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17 CiteULike
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Title
voom: precision weights unlock linear model analysis tools for RNA-seq read counts
Published in
Genome Biology (Online Edition), January 2014
DOI 10.1186/gb-2014-15-2-r29
Pubmed ID
Authors

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

Abstract

Normal linear modeling methods are developed for analyzing read counts from RNA-seq experiments. The voom method estimates the mean-variance relationship of the log-counts, generates a precision weight for each observation, and then enters these into a limma empirical Bayes analysis pipeline. This opens access for RNA-seq analysts to a large body of methodology developed for microarrays. Simulation studies show that voom performs as well or better than count-based RNA-seq methods even when the data are generated according to the assumptions of the earlier methods. Two case studies illustrate the use of linear modeling and gene set testing methods.

Twitter Demographics

The data shown below were collected from the profiles of 56 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 3,012 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 38 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 2903 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 795 26%
Researcher 650 22%
Student > Master 329 11%
Student > Bachelor 231 8%
Student > Doctoral Student 161 5%
Other 417 14%
Unknown 429 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 979 33%
Biochemistry, Genetics and Molecular Biology 755 25%
Medicine and Dentistry 163 5%
Computer Science 144 5%
Immunology and Microbiology 80 3%
Other 374 12%
Unknown 517 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 82. 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 2022.
All research outputs
#442,541
of 22,882,389 outputs
Outputs from Genome Biology (Online Edition)
#284
of 4,125 outputs
Outputs of similar age
#4,793
of 305,692 outputs
Outputs of similar age from Genome Biology (Online Edition)
#14
of 138 outputs
Altmetric has tracked 22,882,389 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,125 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 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 305,692 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 138 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 90% of its contemporaries.