High-throughput methods based on chromosome conformation capture technologies have greatly advanced our understanding of the three-dimensional (3D) organization of genomes and demonstrated that genome architecture strongly influences gene regulation. However, methods to analyze the 3D chromatin spatial organization data are still in their infancy. In this talk, I will first present a wavelet approach for noise reduction in fine-scale chromatin contact frequency maps. In the second part, I will present an empirical Bayes hierarchical model to infer allele-specific chromatin contacts from diploid Hi-C data. Using the zero-inflated Poisson model, our method is able to reconstruct more accurate allele-specific chromatin structures compared to other existing allelic Hi-C analysis approaches.

Prof. Wenxiu Ma