发表机构
Faculty of Mathematics and Computer Science, Transilvania University of Braşov (UNITBV)（布拉索夫特兰西瓦尼亚大学数学与计算机科学学院（UNITBV））
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究将针对自然图像的HiFiC适配为HiFiC-G，通过修改损失项、采用三阶段微调策略，提升了Hi-C接触图谱局部结构的压缩保留效果，但长程区室结构的保留仍受固定大小分块的限制。
AI 中文摘要
我们研究基于GAN的神经编解码器高保真生成式图像压缩（HiFiC，最初为自然照片构建）的损失设计，是否可在有损压缩下适配以保留Hi-C染色质接触图谱中具有生物学意义的结构。标准图像压缩（包括原始形式的HiFiC）针对人类视觉感知优化，但Hi-C接触图谱通常与其数值矩阵文件（.cool/.mcool）一同分布，下游基因组分析工具会直接使用该文件。对人眼而言可接受的激进压缩，仍可能模糊或删除这些工具所依赖的环（loops）、拓扑关联结构域（TAD）边界。我们修改HiFiC的失真项，采用空间加权均方误差（MSE），对生物学显著区域（环、TAD边界、条带、区室结构）赋予更高权重，并添加绝缘分数损失项，直接惩罚TAD边界清晰度的损失。我们描述了一种三阶段微调策略，在不发生灾难性遗忘的情况下，将预训练的HiFiC检查点适配到Hi-C领域。我们在两种细胞系上，同时使用传统图像质量指标（PSNR、SSIM）和基因组领域保留指标（环/TAD/区室/条带保留百分比）评估所得系统HiFiC-G。结果显示，HiFiC-G对局部结构（条带和TAD边界）的保留效果，远优于单独指标所暗示的；而长程A/B区室结构的保留效果仍较差，我们表明该差距与基因组规模相关，且与一个特定架构原因一致：HiFiC-G和原始HiFiC为实现内存效率所依赖的固定大小分块。
英文摘要
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 tools depend on. We modify HiFiC's distortion term with a spatially-weighted MSE that up-weights biologically salient regions (loops, TAD boundaries, stripes, compartment structure) and add an insulation-score loss term that directly penalizes loss of TAD boundary sharpness. We describe a three-phase fine-tuning strategy that adapts a pretrained HiFiC checkpoint to the Hi-C domain without catastrophic forgetting. We evaluate the resulting system, HiFiC-G, using both conventional image-quality metrics (PSNR, SSIM) and genomics-domain preservation metrics (loop/TAD/compartment/stripe preservation percentage) across two cell lines. HiFiC-G preserves local structure, meaning stripes and TAD boundaries, substantially better than the metrics alone would suggest, while long-range A/B compartment structure remains poorly preserved; we show this gap tracks genomic scale and is consistent with a specific architectural cause, the fixed-size tiling that both HiFiC-G and the original HiFiC rely on for memory efficiency.
Comments13 pages, 3 figures, 2 tables. Bachelor's thesis project, Transilvania University of Brasov (UNITBV). Language editing and translation assistance provided using Claude (Anthropic)
