Unicorn: Enhancing Single-Cell Hi-C Data with Blind Super-Resolution for 3D Genome Structure Reconstruction
Authors/Creators
Description
In this study, we present ScUnicorn, a novel blind Super-Resolution framework for scHi-C enhancement. ScUnicorn employs an iterative degradation kernel optimization process, unlike traditional Super-resolution approaches, which rely on downsampling, predefined degradation ratios, or constant assumptions about the input data to reconstruct high-resolution interaction matrices. Hence, our approach more reliably preserves critical biological patterns and minimizes noise. Additionally, we propose 3DUnicorn, a maximum likelihood algorithm that leverages the enhanced scHi-C data to infer precise 3D chromosomal structures.
Files
Dataset_Mouse.zip
Files
(42.6 MB)
| Name | Size | Download all |
|---|---|---|
|
md5:5b59559e9fe0dadee308021a424ad26b
|
922.7 kB | Preview Download |
|
md5:1cfc40fe3bb65b8edca1eba00407583f
|
41.6 MB | Download |
Additional details
Dates
- Updated
-
2025-03-22Removed the draft manuscript file from the repo.