Mixture Modeling for Identifying Spatial Interactions of Chromatins

• Activity Number: 499
• Type: Topic Contributed
• Date/Time: Wednesday, August 1, 2012 : 10:30 AM to 12:20 PM
• Sponsor: WNAR
• Author(s): Liang Niu*+ and Shili Lin
• Companies: The Ohio State University and The Ohio State University

Abstract

The expression of a gene is usually controlled by the regulatory elements in its promoter region. However, it has long been hypothesized that, in complex genomes, such as the human genome, a gene may be controlled by distant enhancers and repressors. A recent molecular technique, 3C (chromosome conformation capture), that uses formaldehyde cross-linking and locus-specific PCR was able to detect physical contacts between distant genomic loci. Such communication is achieved through spatial organization (looping) of chromosomes to bring genes and their regulatory elements into close proximity. Several adaptations of the 3C assay to study genome-wide spatial interactions, including Hi-C and ChIA-PET (chromatin interaction analysis by pair-end tag sequencing), have been proposed. However, due to the enrichment of ligation products on beads, such methods may also detect random collisions in addition to true spatial interactions. In this talk, we will present a mixture model for large-scale genome-wide looping data, which will be casted into a Bayesian framework to facilitate parameter estimation. In particular, we will discuss how to use part of the correlated data to tackle the problem