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X Demographics
Mendeley readers
Attention Score in Context
| Title |
GWAS on your notebook: fast semi-parallel linear and logistic regression for genome-wide association studies
|
|---|---|
| Published in |
BMC Bioinformatics, May 2013
|
| DOI | 10.1186/1471-2105-14-166 |
| Pubmed ID | |
| Authors |
Karolina Sikorska, Emmanuel Lesaffre, Patrick FJ Groenen, Paul HC Eilers |
| Abstract |
Genome-wide association studies have become very popular in identifying genetic contributions to phenotypes. Millions of SNPs are being tested for their association with diseases and traits using linear or logistic regression models. This conceptually simple strategy encounters the following computational issues: a large number of tests and very large genotype files (many Gigabytes) which cannot be directly loaded into the software memory. One of the solutions applied on a grand scale is cluster computing involving large-scale resources. We show how to speed up the computations using matrix operations in pure R code. |
X Demographics
The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 42% |
| United Kingdom | 1 | 8% |
| Norway | 1 | 8% |
| Unknown | 5 | 42% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 50% |
| Scientists | 5 | 42% |
| Practitioners (doctors, other healthcare professionals) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 131 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | <1% |
| France | 1 | <1% |
| Cuba | 1 | <1% |
| United Kingdom | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 126 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 31 | 24% |
| Researcher | 31 | 24% |
| Student > Master | 17 | 13% |
| Professor | 10 | 8% |
| Student > Bachelor | 7 | 5% |
| Other | 24 | 18% |
| Unknown | 11 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 44 | 34% |
| Computer Science | 23 | 18% |
| Biochemistry, Genetics and Molecular Biology | 23 | 18% |
| Medicine and Dentistry | 10 | 8% |
| Mathematics | 7 | 5% |
| Other | 11 | 8% |
| Unknown | 13 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 21. 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 13 September 2022.
All research outputs
#1,674,899
of 24,417,958 outputs
Outputs from BMC Bioinformatics
#312
of 7,530 outputs
Outputs of similar age
#13,874
of 198,584 outputs
Outputs of similar age from BMC Bioinformatics
#8
of 114 outputs
Altmetric has tracked 24,417,958 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,530 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 95% 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 198,584 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 93% of its contemporaries.
We're also able to compare this research output to 114 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 93% of its contemporaries.