Special Colloquium
Liping Tong
University of Washington
Multilocus Lod Scores in Large Pedigrees: Combination of Exact and Approximate Calculations
Abstract: To detect the positions of disease loci, LOD scores need to be calculated
within a (several)
pedigree(s) for a given set of markers at multiple chromosomal positions.
Exact LOD score calculations are often impossible when the size of the
pedigree and the number of markers are both large. In this case, a Markov
Chain Monte Carlo (MCMC) approach is able to provide an approximation.
However, the mixing performance, to provide accurate results, within a
reasonable amount of time, is always a key issue in these MCMC methods. In
our project, we propose a new approach, which divides a large pedigree into
several parts by conditioning
on the haplotypes of some ``key'' individuals. We perform exact calculations
for the descendant parts where more data are often available, and combine
this information to sample the hidden variables for the ancestral parts. We
also improve the ancestral sampling part using a mixture of several
conditional Hidden Markov Chains across loci or meiosis. Our approach is
expected to be useful for a complicated, large pedigree with a lot of
missing data, in which case most current methods cannot give satisfactory
results. The results from simulation studies are encouraging, comparing to
other MCMC methods.
Wednesday January 24, 2007 at 3:00 PM in SEO 636