近日，北京大学席瑞斌课题组发现了可解释的多模态降维框架SpaHDmap提高了空间转录组学的分辨率。相关论文于2026年1月6日发表在《自然—细胞生物学》杂志上。

在这里，课题组介绍了“空间高清嵌入映射”（SpaHDmap），这是一个可解释的降维框架，通过将ST基因表达与高分辨率组织学图像相结合来提高空间分辨率。SpaHDmap将非负矩阵分解纳入深度学习框架，从而能够识别高分辨率空间元序列（嵌入）。

此外，SpaHDmap可以同时分析多个样本，并与各种类型的组织学图像兼容。对合成的、公开的和新测序的来自不同技术和组织类型的ST数据集的广泛评估表明，SpaHDmap可以有效地产生高分辨率的空间元基因组，并检测精细的空间结构。SpaHDmap是一种集成ST数据和组织学图像的强大方法，可以更深入地了解复杂的组织结构和功能。

据介绍，空间转录组学（ST）技术通过捕捉空间背景下的基因表达，彻底改变了组织结构研究。然而，高维ST数据通常具有有限的空间分辨率，并且表现出相当大的噪声和稀疏性，这对破译微妙的空间结构和潜在的生物活动构成了重大挑战。

附：英文原文

Title: The interpretable multimodal dimension reduction framework SpaHDmap enhances resolution in spatial transcriptomics

Author: Tang, Junjie, Chen, Zihao, Qian, Kun, Huang, Siyuan, He, Yang, Yin, Shenyi, He, Xinyu, Ye, Buqing, Zhuang, Yan, Meng, Hongxue, Xi, Jianzhong Jeff, Xi, Ruibin

Issue&Volume: 2026-01-06

Abstract: Spatial transcriptomics (ST) technologies revolutionized tissue architecture studies by capturing gene expression with spatial context. However, high-dimensional ST data often have limited spatial resolution and exhibit considerable noise and sparsity, posing substantial challenges in deciphering subtle spatial structures and underlying biological activities. Here we introduce ‘spatial high-definition embedding mapping’ (SpaHDmap), an interpretable dimension reduction framework that enhances spatial resolution by integrating ST gene expression with high-resolution histology images. SpaHDmap incorporates non-negative matrix factorization into a deep learning framework, enabling the identification of high-resolution spatial metagenes (embeddings). Furthermore, SpaHDmap can simultaneously analyse multiple samples and is compatible with various types of histology images. Extensive evaluations on synthetic, public and newly sequenced ST datasets from various technologies and tissue types demonstrate that SpaHDmap can effectively produce high-resolution spatial metagenes, and detect refined spatial structures. SpaHDmap represents a powerful approach for integrating ST data and histology images, offering deeper insights into complex tissue structures and functions.

DOI: 10.1038/s41556-025-01838-z

Source: https://www.nature.com/articles/s41556-025-01838-z