Demystify Hi-C Data Normalization

Hi-C is a sequencing-based method for profiling the genome-wide chromatin contacts. It has been widely used in studying various biological questions such as gene regulation, chromatin structures, genome assembly, etc. The Hi-C experiments involves a series of biochemistical reactions that may introduce noises to the output. Subsequent data analysis such as read mapping also give rise to noises that affect the interpretation of the final output: a contact matrix, where each element in the matrix denotes the contact strength between any two regions of genome. [Read More]

Similarity measurement of two sets of TADs

Months ago I had this question of comparing TADs from two Hi-C experiments in my research. TAD is short for topologically associated domains, discovered by Dixon et al [1] in 2012, which are regions in the genome that interacts more frequenctly with regions in the domain than outside. The goal of comparing TADs from two Hi-C expriments is to search for differentially interacting regions under two conditions to tease out regions that react to the conditions. [Read More]