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Fully moderated t-statistic in linear modeling of mixed effects for differential expression analysis

Overview of attention for article published in BMC Bioinformatics, December 2019
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

blogs
1 blog
twitter
2 X users

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
25 Mendeley
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Title
Fully moderated t-statistic in linear modeling of mixed effects for differential expression analysis
Published in
BMC Bioinformatics, December 2019
DOI 10.1186/s12859-019-3248-9
Pubmed ID
Authors

Lianbo Yu, Jianying Zhang, Guy Brock, Soledad Fernandez

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 28%
Researcher 4 16%
Student > Bachelor 1 4%
Other 1 4%
Student > Postgraduate 1 4%
Other 0 0%
Unknown 11 44%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 20%
Computer Science 2 8%
Immunology and Microbiology 1 4%
Psychology 1 4%
Medicine and Dentistry 1 4%
Other 1 4%
Unknown 14 56%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 24 December 2019.
All research outputs
#4,065,648
of 23,182,015 outputs
Outputs from BMC Bioinformatics
#1,547
of 7,345 outputs
Outputs of similar age
#94,135
of 458,130 outputs
Outputs of similar age from BMC Bioinformatics
#51
of 224 outputs
Altmetric has tracked 23,182,015 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,345 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 78% 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 458,130 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 224 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.