Estimation of Y haplotype frequencies with lower order dependencies

Abstract

Estimating Y haplotype population frequencies is a demanding task in forensic genetics. Despite the suggestion of various methods, none these have yet reached a level of accuracy and precision that is acceptable to the forensic genetics community. At the basis of this problem is the complex dependency structure between the involved STR loci. Here, we approximate this structure by the use of specific graphical models, namely t-cherry junction trees. We apply trees of order three by which dependencies between three STR loci can be taken into account, thereby extending the Chow-Liu method which is restricted to pairwise dependencies. We show that the t-cherry tree method outperforms the Chow-Liu method as well as the well-established discrete Laplace method in estimation accuracy.

Keywords: Chow–Liu algorithm; Discrete Laplace method; Forensic genetics; Frequency estimation; Graphical models; Y haplotypes; t-cherry junction trees.