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Activity Number:
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281
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Type:
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Contributed
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Date/Time:
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Tuesday, August 8, 2006 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #307195 |
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Title:
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Evaluating the Impact of Family Structure on Estimating Genetic Association Parameters in Family Studies
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Author(s):
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Stefan Boehringer*+ and Ruth Pfeiffer
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Companies:
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National Cancer Institute and National Cancer Institute
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Address:
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6120 Executive Blvd., Rockville, MD, 20852,
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Keywords:
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statistical genetics ; genetic association ; penetrance ; likelihood ; residual correlation ; Alzheimer's
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Abstract:
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Most work on family based association studies between genetic markers and a disease focuses on the problem of testing the null hypothesis of no association. We present a likelihood based approach to estimating association parameters in family-based studies for a true, unobserved disease locus. We show that, assuming the baseline risk of the disease is known, one can estimate the penetrance function under the proper genetic model, the allele frequency of the (unobserved) true disease allele and its linkage disequilibrium with the observed markers. These parameters are not identifiable based on observations on unrelated cases and controls. Extensions can be made to account for additional unlinked disease loci. We evaluate the impact of family structure and ascertainment schemes on the parameter estimates in simulations and apply the method to data on Alzheimer's disease.
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