AbstractBayesian inference has been used for genetic risk calculation. In this traditional method, inheritance events are divided into a number of cases under the inheritance model, and some elements of the inheritance model are usually disregarded. We developed a genetic risk calculation program, GRISK, which contains an improved Bayesian risk calculation algorithm to express the outcome of inheritance events with inheritance vectors, a set of ordered genotypes of founders, and mutation vectors, which represent a new idea for description of mutations in a pedigree. GRISK can calculate genetic risk in a common format that allows users to execute the same operation in every case, whereas the traditional risk calculation method requires construction of a calculation table in which the inheritance events are variously divided in each respective case. In addition, GRISK does not disregard any possible events in inheritance. This program was developed as a Japanese macro for Excel to run on Windows.
[1]
M. Dickie,et al.
Natural mutation rates in the house mouse. Estimates for five specific loci and dominant mutations.
,
1971,
Mutation research.
[2]
L Kruglyak,et al.
Parametric and nonparametric linkage analysis: a unified multipoint approach.
,
1996,
American journal of human genetics.
[3]
Lawrence R. Rabiner,et al.
A tutorial on hidden Markov models and selected applications in speech recognition
,
1989,
Proc. IEEE.
[4]
Susan E. Hodge.
A Simple, Unified Approach to Bayesian Risk Calculations
,
2004,
Journal of Genetic Counseling.