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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A variance component based multi-marker association test using family and unrelated data
|
|---|---|
| Published in |
BMC Genomic Data, March 2013
|
| DOI | 10.1186/1471-2156-14-17 |
| Pubmed ID | |
| Authors |
Xuefeng Wang, Nathan J Morris, Xiaofeng Zhu, Robert C Elston |
| Abstract |
Incorporating family data in genetic association studies has become increasingly appreciated, especially for its potential value in testing rare variants. We introduce here a variance-component based association test that can test multiple common or rare variants jointly using both family and unrelated samples. |
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 % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 3% |
| Brazil | 1 | 3% |
| Unknown | 28 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 40% |
| Student > Ph. D. Student | 6 | 20% |
| Student > Doctoral Student | 3 | 10% |
| Professor | 3 | 10% |
| Student > Master | 2 | 7% |
| Other | 2 | 7% |
| Unknown | 2 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 16 | 53% |
| Mathematics | 4 | 13% |
| Biochemistry, Genetics and Molecular Biology | 2 | 7% |
| Computer Science | 2 | 7% |
| Medicine and Dentistry | 2 | 7% |
| Other | 1 | 3% |
| Unknown | 3 | 10% |
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 12 March 2013.
All research outputs
#17,286,645
of 25,374,917 outputs
Outputs from BMC Genomic Data
#668
of 1,204 outputs
Outputs of similar age
#133,993
of 207,614 outputs
Outputs of similar age from BMC Genomic Data
#10
of 15 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,204 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 34th percentile – i.e., 34% 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 207,614 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.