Year: 2014
Type: article
Abstract: Chromosome conformation capture experiments have led to the discovery of dense, contiguous, megabase-sized topological domains that are similar across cell types and conserved across species. These domains are strongly correlated with a number of chromatin markers and have since been included in a number of analyses. However, functionally-relevant domains may exist at multiple length scales. We introduce a new and efficient algorithm that is able to capture persistent domains across various resolutions by adjusting a single scale parameter. The ensemble of domains we identify allows us to quantify the degree to which the domain structure is hierarchical as opposed to overlapping, and our analysis reveals a pronounced hierarchical structure in which larger stable domains tend to completely contain smaller domains. The identified novel domains are substantially different from domains reported previously and are highly enriched for insulating factor CTCF binding and histone marks at the boundaries.
Source: Algorithms for Molecular Biology
Institutions: University of Pittsburgh, Carnegie Mellon University
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,490
Awards: Fast k-mer Counting to Quantify Gene Expression and Improve Genome Assembly, G3549828030, CAREER: Model-based Reconstruction of Ancient Biological Networks, Better Network Modules: New Tools for Protein Network Analysis, Integrated Interdisciplinary, inter-university PhD Program Computational Biology (T32), Algorithms for Managing Uncertainty in Chromosome Conformation Capture Data, Accurate Computational Detection of Influenza Reassortments, CAREER: Model-based Reconstruction of Ancient Biological Networks
OpenAlex ID: W2109949710