Homo sapiens raw sequence reads of circulating cell-free DNA

Circulating cell-free DNA (cfDNA) offers a non-invasive window into chromatin organization and gene regulation through its fragmentation patterns, which reflect nucleosome positioning. This project focuses on developing novel bioinformatics methodologies to accurately infer nucleosome occupancy from cfDNA sequencing data. By leveraging probabilistic scoring models, we aim to improve the resolution of nucleosome occupancy and cfDNA breakpoint peak detection. Our approach integrates fragmentomics with chromatin state annotations to distinguish between nucleosome spacing in euchromatin and heterochromatin, revealing how chromatin topology influences cfDNA biogenesis. By refining nucleosome peak calling and breakpoint prediction, this methodology aims to enhance liquid biopsy sensitivity for mutation detection and epigenetic profiling.