Supplementary Figure 1: Flow cytometry gating scheme and a data-driven approach to separate samples on the basis of flow cytometry data. | Nature Immunology

Supplementary Figure 1: Flow cytometry gating scheme and a data-driven approach to separate samples on the basis of flow cytometry data.

From: Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry

Supplementary Figure 1

a, Flow cytometry gating: stromal fibroblasts (CD45–PDPN+), monocytes (CD45+CD14+), T cells (CD45+CD3+), and B cells (CD45+CD3–CD19+). b, As a percentage of live cells: synovial T cells, B cells, and monocytes for OA-arthro (OA arthroplasty), RA-arthro (RA arthroplasty), and RA-biopsy (RA biopsy) by flow cytometry. c, Comparison of lymphocytes (T and B cells) and monocytes, as a percentage of live cells by flow cytometry. d, Mahalanobis distance from OA samples. Each dot represents a donor. Each panel highlights the contribution of T cells, B cells, and monocytes to the distance (y axis). We defined leukocyte-rich RA samples as those with Mahalanobis distance from OA greater than 4.5 (dashed line). We identified 19 leukocyte-rich RA, 17 leukocyte-poor RA, and 15 OA samples in our cohort.

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