Spatial Transcriptomics

The increasing popularity of spatial transcriptomics (ST) technologies is enhancing our understanding of the tumor microenvironment (TME). Spatial transcriptomics enables us to map gene expression within the broader tissue architecture, offering the potential to uncover significant interactions between TME elements and cancer vulnerabilities. However, analyzing ST data comes with its unique set of challenges. The high dimensionality of gene expression data, combined with the added spatial dimension, can be overwhelming to analyze, necessitating the use of programming. Explicitly integrating spatial information also poses a significant challenge, as most researchers analyze ST data using non-spatial scRNA-seq pipelines. In this presentation, some of these challenges are illustrated and methods developed by the scientific community to address them are mentioned. Finally, we provide a brief introduction to spatialGE, a web application designed to assist non-data scientists in the exploratory analysis of ST data.