Abstract
Sequencing-based microscopy is a novel, optics-free method for imaging molecules in biological samples using molecular DNA barcodes, spatial networks, and sequencing technologies. Despite its promise, the principles determining how these networks preserve spatial information are not fully understood. Current validation methods, which rely on comparing reconstructed positions to expected results, would benefit from a deeper understanding of these principles. Here, we introduce the concept of spatial coherence— a set of fundamental properties of spatial networks that quantifies the alignment between topological relationships and Euclidean geometry. Our findings show that spatial coherence is an effective method for evaluating a network’s capacity to maintain spatial fidelity and identify distortions, independent of prior information. This framework provides a cost-effective validation tool for sequencing-based microscopy by taking advantage of the fundamental properties of spatial networks in nanoscale systems.
Publisher
Cold Spring Harbor Laboratory
Cited by
1 articles.
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