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Significance testing in ridge regression for genetic data

Overview of attention for article published in BMC Bioinformatics, September 2011
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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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

blogs
1 blog
twitter
1 tweeter
q&a
3 Q&A threads

Citations

dimensions_citation
45 Dimensions

Readers on

mendeley
161 Mendeley
citeulike
3 CiteULike
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Title
Significance testing in ridge regression for genetic data
Published in
BMC Bioinformatics, September 2011
DOI 10.1186/1471-2105-12-372
Pubmed ID
Authors

Erika Cule, Paolo Vineis, Maria De Iorio

Abstract

Technological developments have increased the feasibility of large scale genetic association studies. Densely typed genetic markers are obtained using SNP arrays, next-generation sequencing technologies and imputation. However, SNPs typed using these methods can be highly correlated due to linkage disequilibrium among them, and standard multiple regression techniques fail with these data sets due to their high dimensionality and correlation structure. There has been increasing interest in using penalised regression in the analysis of high dimensional data. Ridge regression is one such penalised regression technique which does not perform variable selection, instead estimating a regression coefficient for each predictor variable. It is therefore desirable to obtain an estimate of the significance of each ridge regression coefficient.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 161 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 2%
United Kingdom 3 2%
Australia 1 <1%
Italy 1 <1%
France 1 <1%
Indonesia 1 <1%
Belgium 1 <1%
Denmark 1 <1%
Japan 1 <1%
Other 1 <1%
Unknown 146 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 47 29%
Researcher 33 20%
Student > Master 17 11%
Student > Bachelor 13 8%
Student > Doctoral Student 9 6%
Other 27 17%
Unknown 15 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 57 35%
Biochemistry, Genetics and Molecular Biology 19 12%
Mathematics 17 11%
Engineering 10 6%
Psychology 6 4%
Other 31 19%
Unknown 21 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 18. 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 21 June 2020.
All research outputs
#1,166,929
of 15,882,500 outputs
Outputs from BMC Bioinformatics
#310
of 5,760 outputs
Outputs of similar age
#12,356
of 156,415 outputs
Outputs of similar age from BMC Bioinformatics
#3
of 22 outputs
Altmetric has tracked 15,882,500 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,760 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one has done particularly well, scoring higher than 94% 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 156,415 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 92% of its contemporaries.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.