The STRND algorithm is for reconstructing spatial networks of barcodes, in particular, those that don't have distance information built into the edges or relationships between nodes. Instead, STRND uses random walks to sample the area around each node, placing it in a spatial context relative to other nodes. We discovered this approach to be surprisingly robust for most spatial network reconstruction tasks, even when very little is known about how the network was generated, so long as the path between nodes and their distance are somewhat correlated. Read more about it in our Nanoscale paper: Bonet & Hoffecker 2023 And try it out for yourself here: Github STRND repository

This is a tool meant to characterize the composition of an NGS dataset. It uses a limited sample and performs clustering analysis to identify commonly occurring domains/motifs. The tool also enables the user to use reference sequences and probe their extent of representation in the sample. https://github.com/Intertangler/NGS_tool