Project Summary/Abstract Recent advances in single-cell genomic and high content spatial analysis technologies have shed new light on organ and tissue composition, delineating complex tissues and identifying new cell types. However, the data generated by these approaches are becoming increasingly complex. The High Dimensional Cellular and Spatial Analysis Core (HDCSAC – Core C) will work with each project and the Biostatistics and Data Management Core to facilitate the efficient use of single-cell sequencing, high-dimensional tissue imaging, including spatial- transcriptomics, and will oversee the integrated exploratory analysis of high-dimensional datasets. In addition to assisting in testing hypotheses generated by each of the projects, a major role for this core will be to use data- driven approaches for discovery and hypothesis generation. The roles of this core will be split into three aims: For Aim 1, we will support the efficient use of single-cell sequencing across projects. A major focus will be on the use of the 10x Genomics 5’ capture immune profiling platform, which allows for simultaneous detailed profiling of cellular protein (using oligonucleotide tagged antibodies, a.k.a. CITEseq), mRNA, and paired ⍺βTCR sequencing. For Aim 2, we will work with the Fred Hutch Experimental Histopathology core to coordinate multiplex- immunohistochemistry (mIHC) data acquisition and analysis. We will also leverage our recent experience in the use of new and emerging in situ spatial transcriptomics methods to enable novel hypothesis generation and testing related to the detailed architecture of tumor microenvironment within the bone marrow. Lastly, for Aim 3, we will support integrated analysis of flow cytometry and other high-dimensional datasets generated by this Core and each program project.