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Attention Score in Context
| Title |
A new method for estimating the demographic history from DNA sequences: an importance sampling approach
|
|---|---|
| Published in |
Frontiers in Genetics, August 2015
|
| DOI | 10.3389/fgene.2015.00259 |
| Pubmed ID | |
| Authors |
Sadoune Ait Kaci Azzou, Fabrice Larribe, Sorana Froda |
| Abstract |
The effective population size over time (demographic history) can be retraced from a sample of contemporary DNA sequences. In this paper, we propose a novel methodology based on importance sampling (IS) for exploring such demographic histories. Our starting point is the generalized skyline plot with the main difference being that our procedure, skywis plot, uses a large number of genealogies. The information provided by these genealogies is combined according to the IS weights. Thus, we compute a weighted average of the effective population sizes on specific time intervals (epochs), where the genealogies that agree more with the data are given more weight. We illustrate by a simulation study that the skywis plot correctly reconstructs the recent demographic history under the scenarios most commonly considered in the literature. In particular, our method can capture a change point in the effective population size, and its overall performance is comparable with the one of the bayesian skyline plot. We also introduce the case of serially sampled sequences and illustrate that it is possible to improve the performance of the skywis plot in the case of an exponential expansion of the effective population size. |
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 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 21 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 24% |
| Student > Master | 4 | 19% |
| Student > Postgraduate | 3 | 14% |
| Researcher | 3 | 14% |
| Student > Bachelor | 2 | 10% |
| Other | 3 | 14% |
| Unknown | 1 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 11 | 52% |
| Biochemistry, Genetics and Molecular Biology | 6 | 29% |
| Mathematics | 2 | 10% |
| Environmental Science | 1 | 5% |
| Arts and Humanities | 1 | 5% |
| Other | 0 | 0% |
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 07 August 2015.
All research outputs
#18,422,065
of 22,821,814 outputs
Outputs from Frontiers in Genetics
#7,043
of 11,792 outputs
Outputs of similar age
#189,972
of 264,084 outputs
Outputs of similar age from Frontiers in Genetics
#54
of 70 outputs
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