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DTSTAMP:20100211T210000Z
UID:1261494640988@events.msu.edu
CATEGORIES:Conferences / Seminars / Lectures
DTSTART:20100211T210000Z
DTEND:20100212T045900Z
SUMMARY:Set-level Analyses for Genome-wide Association Data
DESCRIPTION:
 In this setting of genome-wide association studies, 
 we propose a method for assigning a measure 
 of significance to pre-defined sets of markers 
 in the genome.  The sets can be genes, 
 conserved regions, or groups of genes such as 
 pathways.  Using the proposed methods and algorithms, 
 evidence for association between a 
 particular functional unit and a disease status 
 can be obtained not just by the presence 
 of a strong signal from a SNP within it, but 
 also by the combination of several simultaneous 
 weaker signals that are not strongly correlated. 
  This approach has several advantages. 
  First, moderately strong signals from different 
 SNPs are combined to obtain a much stronger 
 signal for the set, therefore increasing 
 power.  Second, in combination with methods that 
 provide information on untyped markers, it 
 leads to results that can be readily combined 
 across studies and platforms that might use 
 different SNPs. Third, the results are easy 
 to interpret, since they refer to functional 
 sets of markers that are likely to behave as 
 a unit in their phenotypic effect.  Finally, 
 the availability of gene-level p-values for 
 association is the first step in developing methods 
 that integrate information from pathways 
 and networks with genome-wide association 
 data, and these can lead to a better understanding 
 of the complex traits genetic architecture. 
  Presented by Dan Nicolae, Ph.D. of the 
 University of Chicago as part of the Department 
 of Epidemiology's Spring Seminar Series.\n\n
 Price: free\n
 Sponsor: public\n
 Contact name: Ashley James\n
 Contact phone: 353-8623\n
 Contact email: ajames@epi.msu.edu\n
 for more info visit the web at:\n 
 http://www.epi.msu.edu/seminars.htm\n
LOCATION:C102 East Fee Hall
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