SuperTAD: robust detection of hierarchical topologically associated domains with optimized structural information
Yuwei Zhang, Mengbo Wang, Shuai Cheng Li
Abstract
Topologically associating domains (TADs) are the organizational units of chromosome structures. TADs can contain TADs, thus forming a hierarchy. TAD hierarchies can be inferred from Hi-C data through coding trees. However, the current method for computing coding trees is not optimal. In this paper, we propose optimal algorithms for this computation. In comparison with seven state-of-art methods using two public datasets, from GM12878 and IMR90 cells, SuperTAD shows a significant enrichment of structural proteins around detected boundaries and histone modifications within TADs and displays a high consistency between various resolutions of identical Hi-C matrices.
Topics & Concepts
BiologyComputational biologyComputationCoding (social sciences)HierarchyConsistency (knowledge bases)ChromosomeChromosome conformation captureHistoneComputer scienceTheoretical computer scienceAlgorithmEvolutionary biologyMathematicsGeneticsArtificial intelligenceDNAGeneEnhancerGene expressionStatisticsMarket economyEconomicsGenomics and Chromatin DynamicsBioinformatics and Genomic NetworksGene expression and cancer classification