特征(语言学)
限制
图像分辨率
转录组
计算机科学
人工智能
模式识别(心理学)
构造(python库)
分辨率(逻辑)
空间分析
表达式(计算机科学)
图像(数学)
计算机视觉
数据挖掘
遥感
基因表达
生物
基因
地理
工程类
机械工程
哲学
语言学
生物化学
程序设计语言
作者
Yuwei Hua,Yizhi Zhang,Zhenming Guo,Shan Bian,Yong Zhang
标识
DOI:10.1101/2023.05.04.539342
摘要
Abstract The resolution of most spatially resolved transcriptomic technologies usually cannot attain the single-cell level, limiting their applications in biological discoveries. Here, we introduce ImSpiRE, an image feature-aided spatial resolution enhancement method for in situ capturing spatial transcriptome. Taking the information stored in histological images, ImSpiRE solves an optimal transport problem to redistribute the expression profiles of spots to construct new transcriptional profiles with enhanced resolution, together with imputing the gene expression profiles in unmeasured regions. Applications to multiple datasets confirm that ImSpiRE can enhance spatial resolution to the subspot level while contributing to the discovery of tissue domains, signaling communication patterns, and spatiotemporal characterization.
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