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Mendeley readers
Attention Score in Context
| Title |
Power of association tests in the presence of multiple causal variants
|
|---|---|
| Published in |
BMC Proceedings, November 2011
|
| DOI | 10.1186/1753-6561-5-s9-s63 |
| Pubmed ID | |
| Authors |
Yanming Di, Gu Mi, Luna Sun, Rongrong Dong, Hong Zhu, Lili Peng |
| Abstract |
We show that the statistical power of a single single-nucleotide polymorphism (SNP) score test for genetic association reflects the cumulative effect of all causal SNPs that are correlated with the test SNP. Statistical significance of a score test can sometimes be explained by the collective effect of weak correlations between the test SNP and multiple causal SNPs. In a finite population, weak but significant correlations between the test SNP and the causal SNPs can arise by chance alone. As a consequence, when a single-SNP score test shows significance, the causal SNPs contributing to the power of the test are not necessarily located near the test SNP, nor do they have to be in linkage disequilibrium with the test SNP. These findings are confirmed with the Genetic Analysis Workshop 17 mini-exome data. The findings of this study highlight the often overlooked importance of long-range and weak linkage disequilibrium in genetic association studies. |
Mendeley readers
The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 50% |
| Researcher | 1 | 25% |
| Other | 1 | 25% |
| Student > Master | 1 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Mathematics | 1 | 25% |
| Biochemistry, Genetics and Molecular Biology | 1 | 25% |
| Agricultural and Biological Sciences | 1 | 25% |
| Sports and Recreations | 1 | 25% |
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 29 April 2013.
All research outputs
#15,274,524
of 22,714,025 outputs
Outputs from BMC Proceedings
#209
of 374 outputs
Outputs of similar age
#162,757
of 240,282 outputs
Outputs of similar age from BMC Proceedings
#16
of 44 outputs
Altmetric has tracked 22,714,025 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 374 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 31st percentile – i.e., 31% 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 240,282 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.