Fig. 1

Ensemble and single-cell Hi-C computational methods. Top: a population of cells gives rise to a dense Hi-C heatmap, consisting of contact frequencies between all pairs of loci in the genome. The heatmap is typically colored according to the contact frequency, such that red colors indicate a high number of contacts and blue colors indicate a low number of contacts. This heatmap can be used to construct a single consensus structure or to computationally construct a set of deconvoluted structures that, in aggregate, describe the ensemble Hi-C heatmap. Middle: both ensemble Hi-C and single-cell Hi-C can be used to identify three-dimensional (3D) interactions between pairs of elements. For ensemble Hi-C, this is performed by using statistical models to infer significant interactions. In single-cell Hi-C, interactions are inferred directly. Bottom: multiple single cells are analyzed by single-cell Hi-C, giving rise to one contact matrix per cell. The contact matrix is typically visualized such that a contact is highlighted by a blue dot; the matrix shows sparse interaction patterns within the chromosomes. Each single-cell Hi-C contact matrix can then be used to reconstruct the corresponding 3D structures. The ensemble Hi-C heatmap is from [93]. (Single-cell Hi-C contact maps are adapted from [35])