ENT3C: an entropy-based similarity measure for Hi-C and micro-C derived contact matrices

Xenia Lainscsek, Leila Taher*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Hi-C and micro-C sequencing have shed light on the profound importance of 3D genome organization in cellular function by probing 3D contact frequencies across the linear genome. The resulting contact matrices are extremely sparse and susceptible to technical- and sequence-based biases, making their comparison challenging. The development of reliable, robust and efficient methods for quantifying similarity between contact matrices is crucial for investigating variations in the 3D genome organization in different cell types or under different conditions, as well as evaluating experimental reproducibility. We present a novel method, ENT3C, which measures the change in pattern complexity in the vicinity of contact matrix diagonals to quantify their similarity. ENT3C provides a robust, user-friendly Hi-C or micro-C contact matrix similarity metric and a characteristic entropy signal that can be used to gain detailed biological insights into 3D genome organization.

Original languageEnglish
Article numberlqae076
JournalNAR Genomics and Bioinformatics
Volume6
Issue number3
DOIs
Publication statusPublished - 1 Sept 2024

ASJC Scopus subject areas

  • Structural Biology
  • Molecular Biology
  • Genetics
  • Computer Science Applications
  • Applied Mathematics

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