Mapping Averaged Pairwise Information (MAPI): a new exploratory tool to uncover spatial structure

摘要

1. Visualisation of spatial networks based on pairwise metrics such as (dis) similarity coefficients provides direct information on spatial organisation of biological systems. However, for large networks, graphical representations are often unreadable as nodes (samples), and edges (links between samples) strongly overlap. We present a new method, MAPI, allowing translation from spatial networks to variation surfaces.