DEVELOPING COMPUTATIONAL TOOLS TO EXPLORE CHROMATIN DYNAMICS

The three-dimensional organization of the genome shapes gene regulation, ultimately affecting development and disease. Chromosome conformation capture technologies like Hi-C have transformed our ability to map this at a genome-wide scale. These approaches have revealed that chromatin loops play central roles in connecting enhancers with promoters, insulating genes from improper activation, and enabling cell-type-specific transcription. With wider adoption of these methods, we are discovering how structural variation, environmental cues, and disease states reshape the 3D genome in ways that alter cellular identity and function.Despite this progress, major barriers remain. Hi-C experiments are costly and sequencing-intensive, restricting their scalability. The data produced is noisy and sparse, making it difficult to distinguish true loops from background signal. Although powerful statistical frameworks exist for gene expression and differential loop detection, their accuracy hinges on the quality of the underlying data, and very little guidance exists on how to design experiments that will provide datasets with the necessary statistical rigor. These problems limit how effectively researchers can plan, analyze, and interpret 3D genomics experiments.I have developed computational tools that strengthen both the experimental and analytical sides of exploring the dynamics of 3D chromatin structure. Hi-C Poweraid is a web application that provides quantitative guidance for experiment design by estimating sequencing depth and replicate requirements needed for well-powered differential loop detection. Loopcity is an R/Bioconductor package for identifying interactions of groups of loops, enabling investigation of higher-order chromatin communities and their dynamics across conditions. These tools reveal that deeper sequencing than is typically performed is often required to detect condition-specific loop changes, particularly for subtle differences or long-range interactions, and they provide recommendations for planning future experiments accordingly. They also show that chromatin communities act cooperatively to influence regulation, underscoring their importance as a distinct and relatively underexplored layer of genome organization. Overall, this work advances both experimental design and biological insight, enabling new explorations of 3D genome dynamics across conditions and its impact on gene regulation, disease, and human health.