Exploring Chromatin Interaction Between Two Human Cell Types and Different Normalization Techniques for HI-C Data

In regulating gene expression and identifying relevant biomarkers for diseases like cancer, chromatin interaction plays a crucial role. Thus, the volume of HiC data is rapidly increasing as researchers strive to understand chromatin interaction. Most of the work focused on using a genome browser to visualize Hi-C data and genomic features for chromatin conformation. However, comparing chromatin connection and how much similarity exists between different cell types is still unexplored. As a result, this work used the Pearson and Spearman R correlation technique to investigate the similarities between Human ES and IMR90 Fibroblast cell types. By splitting Hi-C data into small subsets, we discovered that both cells have a significant degree of resemblance. Finally, we compared four different normalization methods based on their coefficient of variation results and running time on Hi-C data. Results demonstrate that min absolute scaling is better for Hi-C data as it has a low coefficient of variation than other methods and can perform fast for large Hi-C data.