HiFiC-G: Adapting HiFiC for Hi-C Contact Matrices
We study whether the loss design of High-Fidelity Generative Image Compression (HiFiC), a GAN-based neural codec originally built for natural photographs, can be adapted to preserve biologically meaningful structure in Hi-C chromatin contact maps under lossy compression. Standard image compression, including HiFiC in its original form, optimizes for human visual perception; but a Hi-C contact map is normally distributed together with its numeric matrix file (.cool/.mcool), which downstream genomic analysis tools consume directly. Aggressive compression that looks acceptable to the eye can nonetheless blur or delete loops and topologically associating domain (TAD) boundaries that these too...
| Authors | Andre Antonio Straton |
|---|---|
| Primary category | eess.IV |
| Published | 19 August 2026 |
| Last updated at source | 19 August 2026 |
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