LPAD: using network construction and label propagation to detect topologically associating domains from Hi-C data

Author:

Liu Jian1,Li Pingjing1,Sun Jialiang12,Guo Jun3

Affiliation:

1. College of Computer Science, Nankai University , Tianjin 300071 , China

2. Centre for Bioinformatics and Intelligent Medicine, Nankai University , Tianjin 300071 , China

3. College of Software, Northeastern University , Shenyang 110819 , China

Abstract

Abstract With the development of chromosome conformation capture technique, the study of spatial conformation of a genome based on Hi-C technique has made a quantum leap. Previous studies reveal that genomes are folded into hierarchy of three-dimensional (3D) structures associated with topologically associating domains (TADs), and detecting TAD boundaries is of great significance in the chromosome-level analysis of 3D genome architecture. In this paper, we propose a novel TAD identification method, LPAD, which first extracts node correlations from global interactions of chromosomes based on the random walk with restart and then builds an undirected graph from Hi-C contact matrix. Next, LPAD designs a label propagation-based approach to discover communities and generates TADs. Experimental results verify the effectiveness and quality of TAD detections compared with existing methods. Furthermore, experimental evaluation of chromatin immunoprecipitation sequencing data shows that LPAD performs high enrichment of histone modifications remarkably nearby the TAD boundaries, and these results demonstrate LPAD’s advantages on TAD identification accuracy.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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