Tissues and organs of multicellular organisms are spatially organised by the compartmentalisation of cell types and subpopulations that are coordinated in internal gene regulatory networks, and by signalling from their surrounding tissue environment. In order to perform a subset of biologic processes, these cells differ in terms of localisation, morphology and gene expression patterns. 1 The development of single-cell methods has enabled studies that can retain cellular properties and heterogeneity at a single-cell resolution, which has led to a more detailed understanding of physiologic and disease conditions. 2 One of the most popular methods, single-cell RNA-sequencing (scRNA-seq), has made it possible to profile the whole transcriptome of each individual cell. 3,4 However, it results in the loss of information on spatial relationships among the cell populations since it entails dismantling of the original tissue into single-cell suspensions through mechanical and enzymatic dissociation steps, which could perturb or alter the cell's gene expression. 5 Recently, various techniques have been developed aiming for transcriptome mapping while preserving the spatial location of the expressed transcripts within intact tissues. 6 These methods, collectively known as spatial transcriptomics (ST), have been voted as the method of the year 2020 by Nature Methods and expect to provide remarkable novel insights in the