ArticlebioRxiv : the preprint server for biology2026
Annotating Interchromosomal Interactions at Sub-Megabase Resolution Using Network Clustering Coefficients.
Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Specific interchromosomal interactions involve communication between non-homologous chromosomes, enabling coordinated genomic activities such as gene regulation. However, because these communications are often embedded within a nonspecific and noisy background of contact interactions, it is essential to annotate these interaction patterns at the resolution of genomic positions. Such annotation facilitates clean visualization and comparison with linear genomic features to reveal underlying biological functions. We developed and validated a set of network-based metrics as cross-chromosomal interaction descriptors that bridge complex 3D genome structures and 1D functional genomics. By utilizing graph-theoretic representations, these network-based features succinctly summarize complex inter-chromosomal relationships. We constructed a graph representation of contact interactions derived from Hi-C data and implemented three annotations that capture the distinct "many-body" nature of the interactions. Among these, we demonstrate that ΔC4 (a cis-contact-mediated 4-cycle interaction metric) is superior to both ΔC3 (a cis-contact-mediated 3-cycle metric) and C4
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