Cancer genomes evolve by acquiring a diverse repertoire of DNA mutations, copy number aberrations (CNAs), and large chromosomal rearrangements, giving rise to genetically diverse clonal lineages. Decoupling and quantifying genetic heterogeneity and spatial cues within a tumor is critical for understanding the basis for tumor progression and response to therapies. The goals of PI Chen’s IMAT project are to develop Slide-seq into a high-resolution spatial genomics platform for cancer precision medicine. This project seeks to develop robust protocols, pipelines and computational algorithms to democratize spatial transcriptomic profiling for clinical specimens and demonstrate them across tumor types, working directly in the clinical setting. The goals of PI Raphael’s ITCR project are to develop a comprehensive, user-friendly, and modular software suite for tumor heterogeneity and clonal evolution studies across space, time, and genomic scale using data from both bulk and single-cell sequencing technologies. Here, we seek to merge we will develop an integrated experimental and computational platform to analyze the spatial organization of clones in tumor samples. This platform will combine the Slide-RNA-SeqV2 and Slide-DNA-seq technologies under development in PI Chen’s IMAT project with customized computational algorithms that extend methods developed in PI Raphael’s ITCR project.