1 Introduction

1.1 Motivation

The spatialHeatmap package provides functionalities for visualizing cell-, tissue- and organ-specific data of biological assays by coloring the corresponding spatial features defined in anatomical images according to quantitative abundance levels of measured biomolecules, such as transcripts, proteins or metabolites (Zhang et al. 2024). A color key is used to represent the quantitative assay values and can be customized by the user. This core functionality of the package is called a spatial heatmap (SHM) plot. Additional important functionalities include Spatial Enrichment (SE), Spatial Co-Expression (SCE), and Single Cell to SHM Co-Visualization (SC2SHM-CoViz). These extra utilities are useful for identifying biomolecules with spatially selective abundance patterns (SE), groups of biomolecules with related abundance profiles using hierarchical clustering, K-means clustering, or network analysis (SCE), and to co-visualize single cell embedding results with SHMs (SCSHM-CoViz). The latter co-visualization functionality (Figure 1E) is described in a separate vignette called SCSHM-CoViz.

The functionalities of spatialHeatmap can be used either in a command-driven mode from within R or a graphical user interface (GUI) provided by a Shiny App that is part of this project. While the R-based mode provides flexibility to customize and automate analysis routines, the Shiny App includes a variety of convenience features that will appeal to experimentalists and users less familiar with R. The Shiny App can be used on both local computers as well as centralized server-based deployments (e.g. cloud-based or custom servers). This way it can be used for both hosting community data on a public server or running on a private system. The core functionalities of the spatialHeatmap package are illustrated in Figure 1.