JSM 2005 - Toronto

Abstract #302597

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 497
Type: Invited
Date/Time: Thursday, August 11, 2005 : 10:30 AM to 12:20 PM
Sponsor: IMS
Abstract - #302597
Title: Mixture Modeling for Genome-wide Localization of Transcription Factors
Author(s): Sunduz Keles*+
Companies: University of Wisconsin, Madison
Address: 1300 University Avenue, Madison, WI, 53705, USA
Keywords: Genomics ; Mixture Modeling ; Microarrays ; Transcription regulation ; ChIP-chip data ; Hierarchical Models
Abstract:

Chromatin immunoprecipitation followed by DNA microarray analysis (ChIP-chip methodology) is an efficient way of mapping genome-wide protein-DNA interactions. Data from tiling arrays encompass DNA-protein interaction measurements on thousands or millions of short oligonucleotides across a whole chromosome or genome. We propose a new likelihood-based method for analyzing ChIP-chip data. This method is motivated by the widely used two-component multinomial mixture model of regulatory motif detection problem and utilizes a hierarchical mixture model of binding intensities while incorporating apparent spatial structure of the data. Individual probes within a genomic region are allowed to have different localization rates accommodating different binding affinities. Furthermore, fixed window size assumption, which is commonly used when computing a test statistic for these type of spatial data, is relaxed by imposing a distribution on the window size. Simulations and real data applications investigating the operating characteristics of the method will be presented.

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