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X Demographics
Mendeley readers
Attention Score in Context
| Title |
AdmixKJump: identifying population structure in recently diverged groups
|
|---|---|
| Published in |
Source Code for Biology and Medicine, February 2015
|
| DOI | 10.1186/s13029-014-0031-1 |
| Pubmed ID | |
| Authors |
Timothy D O’Connor |
| Abstract |
Correctly modeling population structure is important for understanding recent evolution and for association studies in humans. While pre-existing knowledge of population history can be used to specify expected levels of subdivision, objective metrics to detect population structure are important and may even be preferable for identifying groups in some situations. One such metric for genomic scale data is implemented in the cross-validation procedure of the program ADMIXTURE, but it has not been evaluated on recently diverged and potentially cryptic levels of population structure. Here, I develop a new method, AdmixKJump, and test both metrics under this scenario. |
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 % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 10% |
| Unknown | 9 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 40% |
| Researcher | 4 | 40% |
| Lecturer | 1 | 10% |
| Student > Master | 1 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 5 | 50% |
| Mathematics | 1 | 10% |
| Computer Science | 1 | 10% |
| Psychology | 1 | 10% |
| Earth and Planetary Sciences | 1 | 10% |
| Other | 1 | 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 24 March 2015.
All research outputs
#20,265,771
of 22,796,179 outputs
Outputs from Source Code for Biology and Medicine
#111
of 127 outputs
Outputs of similar age
#296,500
of 352,408 outputs
Outputs of similar age from Source Code for Biology and Medicine
#4
of 6 outputs
Altmetric has tracked 22,796,179 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 127 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.