Royal Statistical Society Highland Local Group

	Meeting announcements





Joint Meeting with St Andrews University

Wednesday May 10th
speakers: David Balding and Christine Hackett

ABSTRACTS:

Genealogical Modelling to Locate Disease Genes from Case-Control Data

David Balding
Department of Applied Statistics
University of Reading

Many methods for locating disease genes are based on genetic and
phenotypic data from extended families affected by the
disease. However, these are limited in their accuracy by the small
number of recombination events underlying even a very large family
tree. In contrast, the genealogical tree underlying a population
sample of case chromosomes offers many more recombinations, but the
problem now is that the tree is unknown. This is problematic because
the case chromosomes are not mutually independent; for example, some
but not others will have been affected by particular mutation or
recombination events in the past. Drawing valid inferences from these
data about disease gene location requires an assessment of the
patterns of dependence in the data due to sharing of ancestry, which
in turn requires accounting for the effects of the underlying
genealogical tree. Much of the recent literature simply ignores the
dependence problem, leading to over-optimistic assessments of
uncertainty in the inferred location. Recently some authors have
offered approximations to take the dependence into account. We propose
explicitly modelling the genealogical tree underlying the sample of
case chromosomes, within the coalescent modelling framework. We
implement Bayesian inference under the model via Markov chain Monte
Carlo. This is joint work with Andrew Morris and John Whittaker, and
is funded by Pfizer UK.


   Statistical methods for linkage analysis and QTL mapping in
                               plants

Christine Hackett
BIOSS
Scottish Crop Research Institute

The association between genetics and statistics is long-standing and
many important statistical concepts were developed, for example by
Galton, Pearson and above all Fisher, in response to questions
motivated by genetics. There were many important developments in
statistical genetics in the period 1908-1940's, but analyses from this
period tend to involve characters affected by a single gene. Because
there are a relatively small number of such characters, practical
analysis was limited. In the last 25 years, developments in molecular
biology mean that variation can be observed in the DNA of an
organism, giving a virtually unlimited supply of molecular markers
whose inheritance can be followed.

One use of molecular markers is to develop a linkage map of a species,
with positions along each chromosome labelled by molecular markers.
Such a map enables the geneticist to locate genes controlling
important traits relative to the markers, particularly quantitative traits
i.e. those  controlled by a large number of genes, and affected by the
environment. For quantitative traits, e.g yield or height, a continuous
response is observed, and the effects of the individual genes  (referred
to as quantitative trait loci or QTLs) cannot be observed directly.
Mapping studies have been performed in man, domestic animals and
agricultural and forest crops. The ease with which experimental
crosses can be made and large numbers of offspring raised mean that
agricultural crops are the simplest subjects for mapping studies.

This talk will review the modelling of recombination between molecular
markers, which forms the basis for estimating a linkage map. From
there, statistical methods for QTL mapping will be discussed. These
are based on mixture models, and thresholds for significance testing
need to considered carefully. Some current work on QTL analysis for
multiple traits and multiple environments will be described.


particulars:
Place :- Lecture Theatre B of the
Mathematical Institute. Timings :- Christine at 3.15 and David at 4.45.
Tea around 4.30 and the meal at 6.30.
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Wednesday June 7th


AGM and committee meeting 
3pm Rm 347 Meston Building University of Aberdeen

6Pm Rm 302 Meston Building King's College University of Aberdeen

Mr Roger Black
Head of the Scottish Cancer Intelligence Unit



Developments in Health Statistics in Scotland

The 1990s has seen unprecedented demand for statistical information on
health and health services in Scotland.  This has been mainly due to:

*	the Scottish Parliament
*	public and media concern about the effectiveness of services such as
screening programmes
*	an acceptance by clinicians that involvement in local audit,
clinical trials and other work in the field of clinical effectiveness tends
to improve services
*	a requirement by managers to inform decision making in the context
of major organisational change, such as the formation of NHS Trusts

This presentation will describe the evolution of the Information and
Statistics Division
of the NHS in Scotland in response to these challenges, drawing on examples
from the field of cancer.  Current developments, including the impact of the
White Paper on National Statistics, will also be discussed.

tea at 5.45

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	web page:http://www.maths.abdn.ac.uk/maths/department/rss/highlands.html
	
_______________________________________________________

Dr Andrew B. Lawson
Department of Mathematical Sciences
University of Aberdeen
Aberdeen
AB24 3UE
UK

phone: 44-1224-272615 (voice mail)
fax: 44-1224-272607
email: [log in to unmask]
web page: 
www.maths.abdn.ac.uk/maths/department/staff/pages/lawson_a.html

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