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SUMMARY:Ancestral Recombination Graphs for Missing and Removable Data - La
 m\, F (UC\, Davis)
DTSTART:20110621T094000Z
DTEND:20110621T100000Z
UID:TALK31804@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:Recombination is a widespread feature of genomes and the study
  of recombination patterns is an important component in the design and ana
 lysis of disease association studies. Advances in algorithms for studying 
 recombination must take into consideration the increasing size of data in 
 both population size and number of sites typed. The goal of our work is to
  develop and implement algorithms to analyze recombination events in data 
 that cannot be analyzed by existing methods\, including data sets that are
  too large or data sets that include missing entries. We demonstrate a bra
 nch and bound approach that is practical\, robust\, and efficient\, and fu
 rthermore show that the approach can be extended to analyze recombination 
 bounds on circular data and input data with missing entries. We apply our 
 methods to analyze simulated data and a benchmark lipoprotein gene and fin
 d that by including sites ignored in previous analysis (due to missing ent
 ries)\, the amount of overall detected reco mbination can be increased ove
 r prior methods. \n
LOCATION:Seminar Room 1\, Newton Institute
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