Title: "An efficient algorithm for simulating coalescence with recombination"

Speaker: Dr. Katy Simonsen

Place: SMITH 108; Tuesday, 4:30pm

Abstract

In population genetics, the coalescent process is an important model by
which the variability of DNA sequence data can be understood.
Coalescent models incorporating genetic recombination have for the last
20 years played an important role in understanding the effect of linkage
on genetic variability in natural populations, both theoretically and
via simulation. For example, coalescence with recombination can be used
to simulate the SNP marker data used to detect association with diseases
and traits in humans and other non-experimental populations. However,
simulation with such models (including that of Simonsen and Churchill,
1997) has suffered from a common problem: the computational complexity
(computer time and memory needed) increases exponentially with the
number of genetic loci involved, and with the population size and
recombination rate. Thus such simulations have been limited to small
numbers of loci encompassing small regions of the genome. This
motivates the development of a much more efficient computer algorithm
for such simulations, whose complexity is only polynomial in the
parameters. I will describe the special structure of the model that
made such efficiency possible, and give some timing results to show that
the desired efficiency has been achieved. This new algorithm will
enable the simulation of genetic data on a genome-wide scale.

See http://www.stat.purdue.edu/~doerge/BIOINFORM.D/SPRING04/sem.html
for a full scheule of BIOINFORMATICS SEMINARS.