↓ Skip to main content

Deep mixed model for marginal epistasis detection and population stratification correction in genome-wide association studies

Overview of attention for article published in BMC Bioinformatics, December 2019
Altmetric Badge

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 (77th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

news
1 news outlet

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
37 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Deep mixed model for marginal epistasis detection and population stratification correction in genome-wide association studies
Published in
BMC Bioinformatics, December 2019
DOI 10.1186/s12859-019-3300-9
Pubmed ID
Authors

Haohan Wang, Tianwei Yue, Jingkang Yang, Wei Wu, Eric P. Xing

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 30%
Researcher 5 14%
Student > Master 2 5%
Student > Bachelor 2 5%
Lecturer 1 3%
Other 3 8%
Unknown 13 35%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 16%
Computer Science 6 16%
Agricultural and Biological Sciences 5 14%
Environmental Science 1 3%
Immunology and Microbiology 1 3%
Other 2 5%
Unknown 16 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 03 January 2020.
All research outputs
#4,261,403
of 23,184,056 outputs
Outputs from BMC Bioinformatics
#1,626
of 7,345 outputs
Outputs of similar age
#99,486
of 457,586 outputs
Outputs of similar age from BMC Bioinformatics
#50
of 219 outputs
Altmetric has tracked 23,184,056 research outputs across all sources so far. Compared to these this one has done well and is in the 80th 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 77% 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 457,586 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 77% of its contemporaries.
We're also able to compare this research output to 219 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.