A random effect model for reconstruction of spatial chromatin structure. Issue 1 (23rd May 2016)

• Record Type: Journal Article
• Authors: Park, Jincheol; Lin, Shili
• Is Part Of: Biometrics. Volume 73:Issue 1(2017)
• Page Start: 52
• Page End: 62
• Publication Date: 2016-05-23
• Subjects: 3D architecture -- Correlation between counts -- Hi‐C data -- Looping -- Random effect modeling; Biometry -- Periodicals; 570.15195
• DOI: 10.1111/biom.12544
• Languages: English
• ISSNs: 0006-341X

Abstract

Summary: A gene may be controlled by distal enhancers and repressors, not merely by regulatory elements in its promoter. Spatial organization of chromosomes is the mechanism that brings genes and their distal regulatory elements into close proximity. Recent molecular techniques, coupled with Next Generation Sequencing (NGS) technology, enable genome‐wide detection of physical contacts between distant genomic loci. In particular, Hi‐C is an NGS‐aided assay for the study of genome‐wide spatial interactions. The availability of such data makes it possible to reconstruct the underlying three‐dimensional (3D) spatial chromatin structure. In this article, we present the Poisson Random effect Architecture Model (PRAM) for such an inference. The main feature of PRAM that separates it from previous methods is that it addresses the issue of over‐dispersion and takes correlations among contact counts into consideration, thereby achieving greater consistency with observed data. PRAM was applied to Hi‐C data to illustrate its performance and to compare the predicted distances with those measured by a Fluorescence In Situ Hybridization (FISH) validation experiment. Further, PRAM was compared to other methods in the literature based on both real and simulated data.