A cytometric imaging approach called CODEX enables high-parameter multiplexing of antibody-tagged target epitopes, allowing high-parameter imaging datasets of normal and lupus (MRL/lpr) mouse spleens. CODEX uses DNA barcodes, fluorescent dNTP analogs, and in-situ polymerization-based indexing to iteratively render antibody binding events. Fluorescent signals from multiple indexing rounds are combined into multi-channel images, which are then segmented and quantified. A segmentation and linear model algorithm accurately quantifies membrane antigen levels on dissociated cells and tissue sections. CODEX's spatially resolved data enables quantitative characterization of lymphoid tissue architecture, revealing the profound impact of cellular neighborhoods on immune cell receptor expression. Comparing normal murine spleens to those of MRL/lpr mice, extensive and previously uncharacterized splenic cell interaction dynamics were observed. The fidelity of CODEX data analysis allows deep proteomic analysis and systematic characterization of complex tissue architecture in normal and clinically aberrant samples. CODEX extends deep phenotyping capabilities to standard three-color fluorescence microscope platforms, enabling high multiplexed single-cell quantification of membrane protein expression in densely packed lymphoid tissue. Automatic delineation of cell types from multidimensional marker expression and positional data enables deep characterization of cellular niches and their dynamics during autoimmune disease. A rich source of multivariate data is generated for the community to refine algorithms for tissue segmentation, sub-tissue neighborhood analysis, and rare cell type detection. In a simulated multicellular mix, CODEX 15-cycle staining patterns showed comparable quantitative rendering of every cellular batch per cycle with low background and no signal carryover. CODEX was validated using identical 24-antibody panels with mass-cytometry (CyTOF), revealing consistent similarity in lineage-positive populations between CODEX and CyTOF data. A 30-antibody panel identified splenic-resident cell types and applied to cryo-sections of wild-type and MRL/lpr spleens. CODEX data revealed 734,101 30-dimensional single-cell protein marker expression profiles, with 58 phenotypic clusters manually annotated. These clusters were assigned to 27 broadly defined single-cell phenotypic groups, some of which matched major immune cell types. Analysis of cell-cell interactions in splenic tissue revealed significant non-random distribution of cells, with major splenic compartments reflected in two large mutually exclusive clusters of positive associations. The highest degree of association was observed between cells of same phenotypic class, suggesting homotypic adhesion as a major force driving cellular distribution in immune organs. Disease progression in MRL/lpr mice led to significant changes in splenic composition, with increased erythroblasts and B220⁺ DN T cells. These changes were associated with the emergence of novel i-niches. The presence of these cells and new i-niches may have altered the observable biology of theA cytometric imaging approach called CODEX enables high-parameter multiplexing of antibody-tagged target epitopes, allowing high-parameter imaging datasets of normal and lupus (MRL/lpr) mouse spleens. CODEX uses DNA barcodes, fluorescent dNTP analogs, and in-situ polymerization-based indexing to iteratively render antibody binding events. Fluorescent signals from multiple indexing rounds are combined into multi-channel images, which are then segmented and quantified. A segmentation and linear model algorithm accurately quantifies membrane antigen levels on dissociated cells and tissue sections. CODEX's spatially resolved data enables quantitative characterization of lymphoid tissue architecture, revealing the profound impact of cellular neighborhoods on immune cell receptor expression. Comparing normal murine spleens to those of MRL/lpr mice, extensive and previously uncharacterized splenic cell interaction dynamics were observed. The fidelity of CODEX data analysis allows deep proteomic analysis and systematic characterization of complex tissue architecture in normal and clinically aberrant samples. CODEX extends deep phenotyping capabilities to standard three-color fluorescence microscope platforms, enabling high multiplexed single-cell quantification of membrane protein expression in densely packed lymphoid tissue. Automatic delineation of cell types from multidimensional marker expression and positional data enables deep characterization of cellular niches and their dynamics during autoimmune disease. A rich source of multivariate data is generated for the community to refine algorithms for tissue segmentation, sub-tissue neighborhood analysis, and rare cell type detection. In a simulated multicellular mix, CODEX 15-cycle staining patterns showed comparable quantitative rendering of every cellular batch per cycle with low background and no signal carryover. CODEX was validated using identical 24-antibody panels with mass-cytometry (CyTOF), revealing consistent similarity in lineage-positive populations between CODEX and CyTOF data. A 30-antibody panel identified splenic-resident cell types and applied to cryo-sections of wild-type and MRL/lpr spleens. CODEX data revealed 734,101 30-dimensional single-cell protein marker expression profiles, with 58 phenotypic clusters manually annotated. These clusters were assigned to 27 broadly defined single-cell phenotypic groups, some of which matched major immune cell types. Analysis of cell-cell interactions in splenic tissue revealed significant non-random distribution of cells, with major splenic compartments reflected in two large mutually exclusive clusters of positive associations. The highest degree of association was observed between cells of same phenotypic class, suggesting homotypic adhesion as a major force driving cellular distribution in immune organs. Disease progression in MRL/lpr mice led to significant changes in splenic composition, with increased erythroblasts and B220⁺ DN T cells. These changes were associated with the emergence of novel i-niches. The presence of these cells and new i-niches may have altered the observable biology of the