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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Visually integrating and exploring high throughput Phenome-Wide Association Study (PheWAS) results using PheWAS-View
|
|---|---|
| Published in |
BioData Mining, June 2012
|
| DOI | 10.1186/1756-0381-5-5 |
| Pubmed ID | |
| Authors |
Sarah A Pendergrass, Scott M Dudek, Dana C Crawford, Marylyn D Ritchie |
| Abstract |
Phenome-Wide Association Studies (PheWAS) can be used to investigate the association between single nucleotide polymorphisms (SNPs) and a wide spectrum of phenotypes. This is a complementary approach to Genome Wide Association studies (GWAS) that calculate the association between hundreds of thousands of SNPs and one or a limited range of phenotypes. The extensive exploration of the association between phenotypic structure and genotypic variation through PheWAS produces a set of complex and comprehensive results. Integral to fully inspecting, analysing, and interpreting PheWAS results is visualization of the data. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 5% |
| Unknown | 56 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 22 | 37% |
| Student > Ph. D. Student | 19 | 32% |
| Student > Master | 3 | 5% |
| Professor | 2 | 3% |
| Other | 2 | 3% |
| Other | 6 | 10% |
| Unknown | 5 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 19 | 32% |
| Biochemistry, Genetics and Molecular Biology | 13 | 22% |
| Computer Science | 6 | 10% |
| Medicine and Dentistry | 4 | 7% |
| Mathematics | 2 | 3% |
| Other | 4 | 7% |
| Unknown | 11 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 26 July 2012.
All research outputs
#18,310,549
of 22,671,366 outputs
Outputs from BioData Mining
#259
of 307 outputs
Outputs of similar age
#128,570
of 166,795 outputs
Outputs of similar age from BioData Mining
#5
of 5 outputs
Altmetric has tracked 22,671,366 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 307 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one is in the 6th percentile – i.e., 6% of its peers scored the same or lower than it.
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 166,795 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one.