MuSpAn: A Toolbox for Multiscale Spatial Analysis

The generation of spatial data in biology has been transformed by multiplex imaging and spatial-omics technologies, such as single cell spatial transcriptomics. These approaches permit a detailed mapping of cell populations and phenotypes within the tissue context, which reveals that tissues are complex ecosystems that include multiple organisational structures over different length scales. Quantitative methods for maximising the information that can be retrieved from these images have not kept pace with technological advances in platforms, and no standard methodology has emerged for spatial data analysis. Proposed pipelines are often tailored to individual studies, leading to a fragmented landscape of available methods, and no clear guidance about which statistical tools are best suited to a particular research question.

In response to these challenges, we present MuSpAn, a Multiscale Spatial Analysis package designed to provide straightforward access to well-established and cutting-edge mathematical tools for analysing spatial data. MuSpAn provides easy to use, flexible, and interactive access to quantitative methods developed from mathematical fields that include spatial statistics, topological data analysis, network theory, geometry, probability and ecology. Users can construct custom pipelines from tools across these fields to address specific biological problems, or conduct unbiased exploration of data for discovery spatial biology. In summary, MuSpAn is an extensive platform which enables multiscale analysis of spatial data, ranging from the subcellular to the tissue-scale.