Hypergeometric Similarity Measure for Spatial Analysis in Tissue Imaging Mass Spectrometry

Abstract

Tissue imaging mass spectrometry (TIMS) is a data-intensive technique for spatial biochemical analysis. TIMS contributes both molecular and spatial information to tissue analysis. We propose and evaluate a similarity measure, based on the hyper geometric distribution, for comparing m/z images from TIMS datasets, with the goal of identifying m/z values with similar spatial distributions. We compare the formulation and properties of the proposed method with those of other similarity measures, and examine the performance of each measure on synthetic and biological data. This study demonstrates that the proposed hyper geometric similarity measure is effective in identifying similar m/z images, and may be a useful addition to current methods in TIMS data analysis.