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解析空间基因组学数据中的重叠条形码

Untangling overlapping barcodes in spatial genomics data.

作者信息

White Jonathan A, Lu Chuqi, Ombelets Lincoln, Cai Long

机构信息

Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.

Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA.

出版信息

bioRxiv. 2025 Jun 16:2025.06.10.658913. doi: 10.1101/2025.06.10.658913.

Abstract

Difficulty in resolving spatially overlapping barcodes is a major bottleneck for imaging-based spatial genomics methods. Here, we present an approach for untangling overlapping barcodes by using strong encoding and global optimization to reduce spurious solutions resulting from recombinations of barcodes. We demonstrate experimentally that cellular regions with average local densities of 127 barcodes per can be decoded with an estimated FDR of less than , enabling a new type of super-resolution microscopy by coding.

摘要

解析空间重叠条形码的困难是基于成像的空间基因组学方法的主要瓶颈。在此,我们提出一种通过使用强编码和全局优化来减少条形码重组产生的虚假解决方案,从而解开重叠条形码的方法。我们通过实验证明,每 平均局部密度为127个条形码的细胞区域可以以估计小于 的错误发现率进行解码,从而通过编码实现一种新型的超分辨率显微镜技术。

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