This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 581
Type: Contributed
Date/Time: Wednesday, August 4, 2010 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #308328
Title: Efficient Exploration of Multiple ChIP-seq and ChIP-chip Data Sets
Author(s): Hongkai Ji*+
Companies: The Johns Hopkins University
Address: Department of Biostatistics, Baltimore, MD, 21205,
Keywords: ChIP-seq ; Clustering ; Hierarchical model ; ChIP-chip ; Genomics ; Bayesian
Abstract:

ChIP-seq and ChIP-chip are powerful high-throughput technologies to study protein-DNA interactions. Patterns of protein-DNA binding across multiple related ChIP-seq or ChIP-chip data sets provide useful information about the underlying biology (e.g., context dependency of gene regulation, interactions of transcription factors). These patterns can be utilized to improve efficiency of statistical analysis as well. We develop a new approach to discover and utilize the patterns from the huge amount of data. The method involves clustering the data based on their correlation patterns and using the identified clusters to facilitate detecting transcription factor binding sites. Through real data analyses, we illustrate that by jointly analyzing all data sets together rather than looking at each data set separately, the approach can be used to explore the huge data sets efficiently.


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