Topological data analysis reveals principles of chromosome structure throughout cellular differentiation
Sauerwald, N.; Shen, Y.; Kingsford, C.
Show abstract
Three-dimensional chromosome structure has a significant influence in many diverse genomic processes and has recently been shown to relate to cellular differentiation. Many methods for describing the chromosomal architecture focus on specific substructures such as topologically-associating domains (TADs) or compartments, but we are still missing a global view of all geometric features of chromosomes. Topological data analysis (TDA) is a mathematically well-founded set of methods to derive robust information about the structure and topology of data sets, making it well-suited to better understand the key features of chromosome structure. By applying TDA to the study of chromosome structure through differentiation across three cell lines, we provide insight into principles of chromosome folding generally, and observe structural changes across lineages. We identify both global and local differences in chromosome topology through differentiation, identifying trends consistent across human cell lines. AvailabilityScripts to reproduce the results from this study can be found at https://github.com/Kingsford-Group/hictda Contactcarlk@cs.cmu.edu
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