JSM 2005 Online Program

Abstract #304045

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Activity Number:	134
Type:	Contributed
Date/Time:	Monday, August 8, 2005 : 10:30 AM to 12:20 PM
Sponsor:	Biometrics Section
Abstract - #304045
Title:	Statistical Methods for the Identification of Microdeletions of Chromosome Segments
Author(s):	Yan Li*+
Companies:	The University of Chicago
Address:	Department of Statistics, Chicago, IL, 60637, United States
Keywords:	genetics ; hidden markov ; chromosome ; deletion ; microdeletion
Abstract:	Microdeletions, the removal of a chromosome segment of size up to several megabases, play an important role in many genetic diseases. Identifying regions of microdeletion related to a genetic disease could lead us to the causal gene(s) located within the microdeletion. We developed methods for the identification of microdeletions for independently sampled cases and controls in addition to extension to parent-offspring trio data using dense markers. We developed a hidden Markov model for microdeletions. This framework leads to efficient algorithms for likelihood calculation and maximization, which allow us to perform likelihood-based inference (hypothesis testing and confidence interval construction) to detect and localize microdeletions associated with a trait. The model includes gamma-distributed deletion lengths and allows for heterogeneity (i.e., some proportion of the case individuals do not carry deletion). We also take into account the occurrence of long homozygous (matching) segments in the general population by using a two-state, continuous-time Markov chain. This is joint work with M. S. McPeek and C. I. Amos.

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