This dataset accompanies the manuscript titled “A Multi-scale, Multiomic Atlas of Human Normal and Follicular Lymphoma Lymph Nodes”, A. Radtke et al., bioRxiv, 2022. [doi: 10.1101/2022.06.03.494716] The dataset contains the processed scRNA-seq information from human lymph nodes, both normal and from Follicular Lymphoma (FL) patients analyzed in this work as a Seurat object. The scRNA-seq information was saved in the rds format for viewing and analysis using the R programming language (to load it in R: scrna_seq_data <- readRDS("scRNA_seq_data_object.rds")). Additionally, the dataset contains comma-separated-value tables describing human lymph nodes, both normal and from Follicular Lymphoma (FL) patients. The files are formatted using the anatomical structures (AS), cell types (CT), and biomarkers (B), ASCT+B format defined by the Human BioMolecular Atlas Program (HuBMAP) for use with the Reporter visualization tool. Details on the structure of ASCT+B tables and the Reporter tool can be found in the standard operating procedure authored by the ASCT+B working group. ASCT+B Table Details In support of a human reference atlas (Regev et al., 2017; Snyder et al., 2019), the Human BioMolecular Atlas Program (HuBMAP) is creating machine readable tables that catalog the anatomical structures (AS), cell types (CT), and biomarkers (B) found in human organs (Börner et al., 2021). ASCT+B tables facilitate data integration across multimodal assays and support comparisons between normal and diseased tissues. In addition, they are readily visualized with the ASCT+B Reporter, a web based tool. For these reasons, we created 10 ASCT+B tables from the datasets included in our study. To construct these tables, we used the Lymph Node v1.1 ASCT+B table as a starting point. The presence or absence of anatomical structures was determined by visual inspection of images and quantitative image analysis of cellular communities. Certain anatomical structures were absent from the excisional biopsies of FL patients e.g., capsule, medulla, hilum, etc. In contrast, the lack of primary follicles, mantle zones, polarized germinal centers (GC), and negligible interfollicular cortex and paracortex in FL LNs reflects changes arising from malignancy. Cell types were defined based on gene biomarkers from bulk and single cell RNA sequencing (RNA-seq) and protein biomarkers from the highly multiplexed imaging method, IBEX (Radtke et al., 2022; Radtke et al., 2020). Whenever possible, cell types captured across assays were defined by both gene and protein biomarkers. However, several cell types were only profiled by bulk RNA-seq, scRNA-seq, or IBEX imaging. In these instances, only assay-specific biomarkers are included in the ASCT+B tables. Whenever possible, we used agreed upon ontology terms to define cell types; however, our study identified several unique cell types not included in ontology databases such as DC-SIGN+ follicular dendritic cells (FDCs). Furthermore, the Reporter does not allow visualization of similar cell types (DC-SIGN- FDCs versus DC-SIGN+ FDCs) in the same anatomical structure if a shared Cell Ontology (CL) identifier is used (FDC: CL:0000442). In these instances, we removed the CL term to allow the Reporter to display the various subpopulations discovered in this study. Cell types were placed in their respective anatomical structures using domain knowledge, visual inspection of images, and quantitative image analysis. Reporter Usage Instructions Visualizing an individual ASCT+B table: Go to Reporter Launch Playground Click on Upload tab Attach CSV final of ASCT+B table Use the toolbars on the left to adjust display. Typical parameters include: Tree Height (1400),Tree width (1000), Bimodal Distance X (500), and Bimodal Distance Y (50). Toggle between gene and protein biomarkers by clicking drop down menu under Biomarkers tab on left-side of screen. Comparing non-FL and FL tables to the Lymph Node v1.1 ASCT+B table: Go to Reporter Select “go to visualization” to compare new tables to a master table for lymph node Click check box next to lymph node and select version of published master table v1.1 Click submit Click compare button at top right tool bar Attach CSV file of non-FL and FL ASCT+B tables Pick colors Go to bottom of panel and click add Click compare Adjust settings for tree height, tree width, bimodal distance x, bimodal distance y, ontology ID on or off, biomarker type (gene or protein), etc. References Börner, K., Teichmann, S.A., Quardokus, E.M., Gee, J.C., Browne, K., Osumi-Sutherland, D., Herr, B.W., Bueckle, A., Paul, H., Haniffa, M., et al. (2021). Anatomical structures, cell types and biomarkers of the Human Reference Atlas. Nature Cell Biology 23, 1117-1128. Radtke, A.J., Chu, C.J., Yaniv, Z., Yao, L., Marr, J., Beuschel, R.T., Ichise, H., Gola, A., Kabat, J., Lowekamp, B., et al. (2022). IBEX: an iterative immunolabeling and chemical bleaching method for high-content imaging of diverse tissues. Nature Protocols. Radtke, A.J., Kandov, E., Lowekamp, B., Speranza, E., Chu, C.J., Gola, A., Thakur, N., Shih, R., Yao, L., Yaniv, Z.R., et al. (2020). IBEX: A versatile multiplex optical imaging approach for deep phenotyping and spatial analysis of cells in complex tissues. Proc Natl Acad Sci U S A 117, 33455-33465. Regev, A., Teichmann, S.A., Lander, E.S., Amit, I., Benoist, C., Birney, E., Bodenmiller, B., Campbell, P., Carninci, P., Clatworthy, M., et al. (2017). The Human Cell Atlas. Elife 6. Snyder, M.P., Lin, S., Posgai, A., Atkinson, M., Regev, A., Rood, J., Rozenblatt-Rosen, O., Gaffney, L., Hupalowska, A., Satija, R., et al. (2019). The human body at cellular resolution: the NIH Human Biomolecular Atlas Program. Nature 574, 187-192.