这篇文章介绍了一种名为 STAMP（用于揭示空间模式的空间转录组学分析主题建模）的新型计算方法，该方法专门用于处理具有空间背景的高维基因表达测量。STAMP是一种可解释且具有空间感知能力的降维技术，它基于深度生成模型，能够返回具有生物学相关性的低维空间主题及其相关的基因模块。文章通过在从小鼠海马体和肺癌样本到小鼠胚胎发育时间序列等多个数据集上的应用，证明了STAMP在识别生物学相关结构、整合多样本数据以及处理跨不同技术数据集方面的卓越性能和可扩展性，并且在模块连贯性和多样性方面优于其他竞争方法。References: Zhong C, Ang K S, Chen J. Interpretable spatially aware dimension reduction of spatial transcriptomics with STAMP[J]. Nature Methods, 2024, 21(11): 2072-2083.
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