The effect on inferences of population size of the sampling scheme for intraspecific DNA sequences
Lead Research Organisation:
University of Glasgow
Department Name: School of Mathematics & Statistics
Abstract
Variation in samples of DNA sequences from within one species can be extremely informative about the demographic processes that have affected that species, revealing signals of migration patterns and population size changes in the past. The demographic models that are fitted to the data might vary, as might the way the data are used, but one almost ubiquitous assumption is that the samples sequenced in the study are randomly chosen. Yet this is rarely plausible either because random sampling is practically impossible to perform or indeed because the samples for analysis are very consciously selected in some non-random way.
This thesis explores the robustness of a particular flexible class of models used for inference of variable population size, the so-called skyline plot methods, to non-randomness of sampling by taking a simulation approach. Pitfalls of analyses ignoring the sampling scheme are reported and recommendations for the interpretation of such analyses are made.
This thesis explores the robustness of a particular flexible class of models used for inference of variable population size, the so-called skyline plot methods, to non-randomness of sampling by taking a simulation approach. Pitfalls of analyses ignoring the sampling scheme are reported and recommendations for the interpretation of such analyses are made.
Organisations
People |
ORCID iD |
Vincent Macaulay (Primary Supervisor) | |
Suzy Whoriskey (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/N509668/1 | 01/10/2016 | 30/09/2021 | |||
1654065 | Studentship | EP/N509668/1 | 01/10/2015 | 30/09/2019 | Suzy Whoriskey |