English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

A conditional likelihood is required to estimate the selection coefficient in ancient DNA

MPS-Authors
/persons/resource/persons121956

Valleriani,  Angelo
Angelo Valleriani, Theorie & Bio-Systeme, Max Planck Institute of Colloids and Interfaces, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)

2307459.pdf
(Publisher version), 300KB

Supplementary Material (public)
There is no public supplementary material available
Citation

Valleriani, A. (2016). A conditional likelihood is required to estimate the selection coefficient in ancient DNA. Scientific Reports, 6: 31561. doi:10.1038/srep31561.


Cite as: https://hdl.handle.net/11858/00-001M-0000-002A-F4E6-B
Abstract
Time-series of allele frequencies are a useful and unique set of data to determine the strength of natural selection on the background of genetic drift. Technically, the selection coefficient is estimated by means of a likelihood function built under the hypothesis that the available trajectory spans a sufficiently large portion of the fitness landscape. Especially for ancient DNA, however, often only one single such trajectories is available and the coverage of the fitness landscape is very limited. In fact, one single trajectory is more representative of a process conditioned both in the initial and in the final condition than of a process free to visit the available fitness landscape. Based on two models of population genetics, here we show how to build a likelihood function for the selection coefficient that takes the statistical peculiarity of single trajectories into account. We show that this conditional likelihood delivers a precise estimate of the selection coefficient also when allele frequencies are close to fixation whereas the unconditioned likelihood fails. Finally, we discuss the fact that the traditional, unconditioned likelihood always delivers an answer, which is often unfalsifiable and appears reasonable also when it is not correct.