TY - BOOK
T1 - Estimation of mutation rates from paternity cases using a Bayesian network
AU - Vicard, P.
AU - Dawid, A.P.
AU - Mortera, J.
AU - Lauritzen, Steffen Lilholt
PY - 2004
Y1 - 2004
N2 - 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.
AB - 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.
M3 - Book
T3 - Research Report Series
BT - Estimation of mutation rates from paternity cases using a Bayesian network
PB - Department of Computer Science, Aalborg University
CY - Department of Statistical Science
ER -