Genome-wide or high-plex gene expression is important to understand the organism, tissue, and cellular mechanism. From microarrays to next-generation sequencing (RNA-Seq) at the bulk level and then to the single cell level, gene expression studies have undergone a long transition. The current bulk gene expression and pathway-centric approach toward disease and therapeutics is moving toward spatial transcriptomics, which makes it possible to profile gene expression from the cellular microenvironment without any loss of spatial information. Spatial transcriptomics allows us to understand cellular interactions, cell type abundance, and profile expression differences between the region of interest and its microenvironment. The technology is revolutionizing oncology, developmental biology, neuroscience, preclinical studies, and many therapeutic approaches, especially immunotherapy. Taking into consideration the diverse spatial transcriptomics technologies available, the current chapter aims to delineate the NGS assay protocol for Digital Spatial Profiler (DSP) and follow bioinformatics analysis. While the workflow itself has been detailed elsewhere, in this chapter we are focusing on the integration of tissue microarrays, bioinformatics pipelines, and statistical approaches specific to GeoMx RNA assays as well as common errors that can occur while running a DSP RNA assay. The descriptions of these methods refer to the current version of the GeoMX DSP guidebook and GeoMx Data Analysis Manual, which can be downloaded from the documents section of NanoString website. These documents and user guides are continuously improved and updated; hence, it is important to regularly check the company’s website for the most recent version.