Inference In Population Genetics

Specialeforsvar ved Simon Christoffer Ziersen

Titel: Inference In Population Genetics

Abstract: The field of mathematical population genetics has been around since the early part of the 20'th century, but it was not until the early 1990's that computational statistical methods were available for likelihood inference on population genetics data. This paper derives the well-known infinite-sites-model describing DNA-sequence data along with sample probabilities as recursion equations on the states of the model. Two importance sampling schemes, derived by Grffiths-Tavaré and Stephens-Donnelly respectively, are then presented along with a new importance sampler. In the work by Stephens and Donnelly they show that their sampler outperforms the one given by Griffiths and Tavaré in efficiency, and the comparison with the new sampler is thus made with the method presented by Stephens and Donnelly. The new sampler takes into account additional information carried in the DNA-sequence data than does the method of Stephens and Donnelly, thus resulting in efficiency gain.

Vejleder: Carsten Wiuf
Censor: Lars Nørvang Andersen