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                Department of Mathematical Sciences                       
                   The Johns Hopkins University                           
                                                                        
                              SEMINAR                                
                                                                        
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Daniel Naiman                                     September 13, 2001
Department of Mathematical Sciences               304 Whitehead Hall
The Johns Hopkins University                      Preseminar: 3:00 p.m.
                                                  Refreshments: 3:30 p.m.
                                                  Seminar: 4:00 p.m.

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      A GENERAL APPROACH TO GENOME SCANS USING IMPORTANCE SAMPLING

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                             ABSTRACT

It is now a widespread practice for researchers to base conclusions about 
the inheritance of disease by scanning large portions of the genome and 
conducting a vast number of simultaneous hypothesis tests.  A key question 
to address is that of determining the probability of a false rejection. 
This talk will present an approach to approximating the error rate using 
an importance sampling algorithm that is described in Naiman and 
Priebe (2001).  The basic idea is to generate samples conditioned on the 
event that a hypothesis is rejected.  The adaptation of this approach to 
some standard genetics problems will be described, with emphasis on the 
mathematics.  In particular, principles of efficient Monte Carlo simulation 
via fast Fourier transforms, and concepts related to conditioning Gaussian 
samples, will be presented. 

(This is joint work with James Malley (NIH) and Joan Baily-Wilson (CIDR).)