Chromosome Level Piecewise Helical Mixing Model for Recovering Chromatin Folding Structure from HiC-Data

• Activity Number: 463 - SPEED: Statistics in Epidemiology and Genomics and Genetics
• Type: Contributed
• Date/Time: Wednesday, August 2, 2017 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics in Genomics and Genetics
• Author(s): Rongrong Zhang* and Michael Yu Zhu and Ming Hu
• Companies: Prudue University and Purdue University and Cleveland Clinic
• Keywords: chromosome structure ; Bayesian model ; MCMC ; HIC ; mixing model ; piecewise helical curve

Abstract

A fundamental question in Hi-C data analysis is to study spatial organizations of chromosomes. In the previous paper, we proposed a piecewise helical model for inferring 3D chromosomal structure at the topological domain scale of Hi-C data based on the assumption that chromosomal regions exhibit a consensus 3D structure in a cell population. However, this assumption may not be true for modeling the structure of the whole chromosome in the cell population. It's unclear whether the cell population contains one dominant structure or multiple distinct structures with comparable mixture proportions. To study the 3D dynamic structure variations of the whole chromosome, we propose a variant model called CPHM (Chromosome Level Piecewise Helical Mixing Model). CPHM models the uncertainty of the spatial arrangement between the two substructures by a mixture component model, where the structure of each component is modeled by a piecewise helical curve. The weight of each component represents the proportion of that component in a cell population. Our model achieves better performance than existing methods and sheds lights into 3D structure of chromatin folding at the whole chromosome level.