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Article Abstract
Scalable proxies of 3D genome interactions, such as from single-cell co-accessibility or Deep Learning, systematically overestimate long-range chromatin contacts. To correct this bias, we introduce a penalty function grounded in polymer physics, derived by fitting a multi-component power-law model to experimental Hi-C data from maize, rice, and soybean. This correction substantially improves concordance with Hi-C, reduces false-positive rates of long-range interactions by up to 95%, and reveals distinct decay exponents corresponding to different scales of chromatin organization. We provide open-source code and derived parameters to facilitate broad application across plant species.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12393530 | PMC |
| http://dx.doi.org/10.1101/2025.08.20.671329 | DOI Listing |
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