Sequencing-based microscopy captures spatial information as DNA barcode networks. Here, we present a protocol for measuring the spatial quality of such networks by estimating the intrinsic network dimension and Gram-matrix spectral scores from the network’s shortest-path distances. We describe steps for installing the software, inputting the edge list of the network, and computing spatial coherence. We then detail procedures for transforming the network into an image. The pipeline handles fast strategies for large graphs and optionally reconstructs spatial layouts for visualization. For complete details on the use and execution of this protocol, please refer to Fernandez Bonet et al. 1 • A protocol for measuring spatial coherence in sequencing-based microscopy networks • Steps for estimating network dimension, spatial constant, and Gram-matrix spectrum • Guidance on scalable analysis for large networks to reduce computational time complexity • Robust network reconstruction algorithms Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. Sequencing-based microscopy captures spatial information as DNA barcode networks. Here, we present a protocol for measuring the spatial quality of such networks by estimating the intrinsic network dimension and Gram-matrix spectral scores from the network’s shortest-path distances. We describe steps for installing the software, inputting the edge list of the network, and computing spatial coherence. We then detail procedures for transforming the network into an image. The pipeline handles fast strategies for large graphs and optionally reconstructs spatial layouts for visualization.
Bonet et al. (Thu,) studied this question.