AVVISO DI SEMINARIO

************** AVVISO DI SEMINARIO ***************

Nell'ambito del progetto di ricerca europeo "Bayesian networks for forensic inference from genetic markers".

Giovedi' 5 giugno, ore 17,00, Sala del Consiglio (accanto alla Presidenza)

Nuala A. Sheehan,

Department of Epidemiology and Public Health, University of Leicester

terrà presso il Dipartimento di Economia, Università Roma Tre, Via Ostiense 139, un seminario dal titolo

ON THE PERFORMANCE OF A BLOCKING MCMC SAMPLER IN A SIMPLE
GENETIC MAPPING SCENARIO

ABSTRACT

It is well known that algorithms for performing exact probability
and likelihood computations on pedigrees break down in practice
for complex genetic applications.
Markov chain Monte Carlo (McMC) methods can be employed to provide
estimates of the required quantities but although these methods
are not restricted by the complexity of the problem, the estimates
they yield are often unreliable.
With this in mind, we investigate the behaviour of one
particular McMC sampling scheme for the detection of a quantitative
trait locus by linkage with marker data when a few specific aspects of
the problem change.
Although we have chosen a very simple pedigree structure and a
trivial mapping scenario, the problem is sufficiently complicated that
exact methods no longer apply.
Consequently, in order to assess the efficiency of our sampler,
we have carried out a study on a test-bed of simulated datasets.
One question that should always be of interest in these complex
applications is whether a full Bayesian McMC analysis is sufficiently
better than a simpler approximation as to make it worth the extra
computational effort required.

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