A reminder of the next Royal Statistical Society medical section meeting on Tuesday 2nd November at 2pm.
Topic: Statistics in the post genome-wide era.
Date: Tuesday 2nd November 2010, 2pm to 5pm.
Venue: Royal Statistical Society, 12 Errol Street, London. EC1Y 8LX. The nearest underground stations are Barbican, Old Street, Moorgate and Liverpool Street. Please see http://www.rss.org.uk/main.asp?page=1759 for directions.
Genome-wide association studies are now commonly used in medical research. This meeting brings together experts from the pharmaceutical industry and academia to highlight statistical challenges, and discuss issues, illustrated by practical examples.
Speakers and titles:
Chris Harbron, AstraZeneca.
Title: New technologies in the Pharmaceutical Industry, some new statistical challenges and some more familiar ones.
Abstract: New molecular technologies such as genomics and proteomics are starting to show great potential for benefiting the pharmaceutical industry, changing both how drug research is performed and how drugs are used through personalised healthcare. These new technologies present many new statistical challenges, not least because of the sheer quantities of data they generate. However, many of the statistical challenges would be familiar to previous generations of statisticians: good design, data quality and the need to understand uncertainty.
Jenny Barrett, University of Leeds.
Title: Genome-wide association studies: statistical issues and multi-locus analysis methods.
Abstract: Genome-wide association (GWA) studies are used to investigate common genetic susceptibility to disease by analysing hundreds of thousands of genetic variants, spread across the whole genome, in cases and controls. I will discuss some of the statistical issues encountered in GWA studies, especially when combining samples from different countries, laboratories or genotyping platforms. The usual method of statistical analysis for these studies is to consider each variant separately, and I will also present our experiences with two multi-locus methods (Random Forest and pathway analysis). These issues will be illustrated using examples from the GWA study of melanoma we have carried out on behalf of the GenoMEL international melanoma genetics consortium, based on cases and controls from numerous mainly European countries.
John Thompson, University of Leicester.
Title: Strategies for replicating the top hits from a GWAS.
Abstract: Because of their potential for generating false positives, it is essential to replicate the findings of any GWAS. There are a number of strategies that are commonly applied and many of these raise complex statistical questions including, how to select the candidates for replication, how to design the replication study and how to test for replication. Indeed it is not always clear what constitutes replication when the measured genetic variants are correlated and may only indirectly identify the causal variant. The talk will illustrate the methods currently being used to address these problems and question whether they are appropriate.
Attendance is free but it is recommended that you register if interested in attending. To register, please visit www.rss.org.uk, then select "Meetings and Events", "Events Calendar" and then "November". Scroll down the page to select the meeting. Click on the link to register.
For further details please contact meeting organiser: Darren Greenwood, Centre for Epidemiology and Biostatistics, University of Leeds ([log in to unmask]).
There will be time for specific questions after each talk and towards the end of meeting for an open-floor discussion.
Darren Greenwood
Senior Lecturer in Biostatistics
Biostatistics Unit
Centre for Epidemiology & Biostatistics
Level 8, Worsley Building
University of Leeds.
Leeds. LS2 9JT
tel: +44 (0)113 343 1813
fax: +44 (0)113 343 4877
email: [log in to unmask]
http://www.personal.leeds.ac.uk/~hssdg
Please note our short courses in biostatistics:
http://www.leeds.ac.uk/statistical_thinking
And our MSc in Statistical Epidemiology:
http://www.leeds.ac.uk/medhealth/light/teaching/msc_stati
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