Abstract
Determining the expected distribution of the time to the most recent common ancestor of a sample of individuals may deliver important information about the genetic markers and evolution of the population. In this paper, we introduce a new recursive algorithm to calculate the distribution of the time to the most recent common ancestor of the sample from a population evolved by any conditional multinomial sampling model. The most important advantage of our method is that it can be applied to a sample of any size drawn from a population regardless of its size growth pattern. We also present a very efficient method to implement and store the genealogy tree of the population evolved by the Galton-Watson process. In the final section we present results applied to a simulated population with a single bottleneck event and to real populations of known size histories.
| Original language | English |
|---|---|
| Pages (from-to) | 265-271 |
| Number of pages | 7 |
| Journal | Theoretical Population Biology |
| Volume | 80 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Dec 2011 |
Keywords
- Dynamic programming
- Galton-Watson process
- MRCA
- Wright-Fisher model
ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics
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