Estimation of mutation rates from paternity cases using a Bayesian network

P. Vicard, A.P. Dawid, J. Mortera, Steffen Lilholt Lauritzen

Research output: Book/ReportBookResearch

Abstract

We present a statistical model and methodology for making inferences about mutation rates from paternity casework. This takes proper account of a number of sources of potential bias, including hidden mutation, incomplete family triplets, uncertain paternity status and differing maternal and paternal mutation rates, while allowing a wide variety of mutation models. A Bayesian network is constructed to facilitate computation of the likelihood function for the mutation parameters. It can process both full and summary genotypic information, from both complete putative father-mother-child triplets and defective cases where only the child and one of its parents are observed. Detailed analysis of a specific dataset is used to illustrate the effects of the various types of biases, and of the assumed mutation model, on inferences about mutation parameters.
Original languageEnglish
Place of PublicationDepartment of Statistical Science
PublisherDepartment of Computer Science, Aalborg University
Number of pages44
Publication statusPublished - 2004
SeriesResearch Report Series
Number249

Fingerprint

Dive into the research topics of 'Estimation of mutation rates from paternity cases using a Bayesian network'. Together they form a unique fingerprint.

Cite this