PROJECT SUMMARY The Human Immune Monitoring Shared Resource (HIMC-SR) is focused on state-of-the-art immunological assays to discover biomarkers of immune competence, diagnosis, prognosis, and response to therapy or vaccination. The HIMC-SR has two major scientific aims: (1) to provide standardized, comprehensive immune monitoring services at the RNA, protein, and cellular levels and (2) to offer immunological data analysis and consultation services. The HIMC-SR began as a Stanford service center in 2007 and has grown to one of the five largest service centers in the School of Medicine. Technology platforms have expanded to include multiple innovative mass cytometry (CyTOF) panels, highly multiplexed immunoassays using Luminex and Olink platforms, and single- cell genomics assays, including new BD Rhapsody massively parallel single-cell transcriptomics assays, which now include nucleic acid-tagged antibodies (AbSeq), T cell receptor targeting (TCRseq), and multiplexed sample tagging. The HIMC-SR has recently developed novel statistical approaches to address the analysis of the large data sets generated by our assays and their unique characteristics and data structures that need to be addressed. These new tools include an R utility to correct for batch effects and non-specific binding in Luminex assays and a star plot visualization for high-dimensional data such as CyTOF. In 2020, 38% of users were SCI investigators. Members of all programs regularly use the HIMC-SR, with the heaviest use coming from the Cancer Immunotherapy and Hematologic Malignancies programs. The HIMC-SR contributed to 18 cancer- focused publications (5 high-impact). The annual budget of the HIMC-SR is $2,238,919, yet the CCSG request is $57,355. Accordingly, the HIMC-SR leverages extensive institutional support and seeks only 3% from CCSG funds. Future goals of the HIMC-SR include expansion of large-scale single-cell genomics assays on the BD Rhapsody platform; continued development of CyTOF panels to include more channels and new markers, as well as novel quality control measures; development of additional statistical tools and expansion of the Statistical Consulting Service; and further development of the Stanford Data Miner online database to facilitate data integration and retrieval.