Simonds et al 2021 -- Figure 1a-c (CyTOF mass cytometry of human glioma, kidney cancer, sarcoma, PBMC)

Immune profiles were obtained from 39 samples: 19 GBM primary tumor biopsies, 11 RCC primary tumor biopsies (one with paired tumor-adjacent normal tissue and metastatic lesion), 4 sarcoma primary tumor biopsies (one with paired tumor-adjacent normal tissue) and PBMCs from 1 healthy donor (with paired unstimulated and phytohemagglutinin-stimulated aliquots). Single-cell mass cytometry data were acquired using T cell-focused and myeloid-focused antibody panels with 42 markers each (see Materials & Methods and Suppl Tables S2 and S3). Data were filtered on CD45-positive cells and processed using the PhenoGraph + FlowSOM analysis pipeline ("PhenoSOM") to segregate immune cell types into metaclusters and quantify their frequency across samples. The cluster IDs after Step 2 of the PhenoSOM pipeline are attached as CSV files (compressed as ZIP files). A key to link the FCS filenames to the cluster ID CSV files are also attached.
Conclusion:
Dataset from Simonds et al JITC 2021 (http://doi.org/10.1136/jitc-2020-002181)
Notes:
Visit https://github.com/esimonds/PhenoSOM/wiki/Running-the-FR-FCM-Z3HK-demo for a tutorial on how to run PhenoSOM on the files in this experiment to obtain the plots in Figures 1A-1B of Simonds et al JITC 2021.