Visualizing and Understanding Chromatin Interactions Using Self-Organizing Maps

Open Access
Kunz, TImothy Robert
Area of Honors:
Biochemistry and Molecular Biology
Bachelor of Science
Document Type:
Thesis Supervisors:
  • Shaun Mahony, Thesis Supervisor
  • Lorraine Santy, Honors Advisor
  • SOM
  • Self-Organizing Maps
  • Hi-C
  • Chromatin
  • nuclear structure
The Hi-C chromatin interaction assay is a relatively new procedure for collecting data on the 3D conformation of DNA in the nucleus. There are few tools and methods for analyzing and visualizing this data. Presented herein is a novel approach to chromatin interaction analysis based on the Self-Organizing Map (SOM) algorithm. This approach gives a more intuitive visualization of the data and serves as a platform for assessing correlations between various genomic activities and chromatin structure. The SOM algorithm provides a two-dimensional grid on which chromatin interactions indicated in Hi-C data are visualized. The resulting data structure can then be used to assess the relationships between genomic biochemical activities (e.g. transcription, histone modifications, protein-DNA binding, etc.) and the organization of the chromatin. Given a set of genomic coordinates corresponding to a given biochemical activity, the degree to which this activity is segregated or compartmentalized in chromatin interaction space can be intuitively visualized on the SOM grid and quantified using modified Lorenz curve analysis. We demonstrate the utility of our approach for exploratory analysis of genome compartmentalization using human high-resolution Hi-C datasets.