ScENCORE: leveraging single-cell epigenetic data to predict chromatin conformation using graph embedding.

ABSTRACT: Dynamic compartmentalization of eukaryotic DNA into active and repressed states enables diverse transcriptional programs to arise from a single genetic blueprint, whereas its dysregulation can be strongly linked to a broad spectrum of diseases. While single-cell Hi-C experiments allow for chromosome conformation profiling across many cells, they are still expensive and not widely available for most labs. Here, we propose an alternate approach, scENCORE, to computationally reconstruct chromatin compartments from the more affordable and widely accessible single-cell epigenetic data. First, scENCORE constructs a long-range epigenetic correlation graph to mimic chromatin interaction frequencies, where nodes and edges represent genome bins and their correlations. Then, it learns the node embedd

SUBMITTER: Duan Z 

PROVIDER: S-EPMC10944576 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature