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Fig. 2 | BMC Bioinformatics

Fig. 2

From: CITEViz: interactively classify cell populations in CITE-Seq via a flow cytometry-like gating workflow using R-Shiny

Fig. 2

CITEViz analysis of PBMC CITE-Seq data. A Identification of CD4-expressing T-cells using CD4-positive and CD3-positive cells, B Identification of CD14-expressing monocyte cells with CD14-positive and CD11b-positive markers, C 2-layer gate that selects for CD8 T-cells. The first gate consists of CD3-positive cells, followed by a CD4-negative and CD8-positive gate. D Example back-gate of natural killer cells shown in an ADT Feature Plot with features of CD3and CD56. E Single-feature expression plot of CD8 protein levels. F 2-feature co-expression plot using CD16 and CD14 to show population heterogeneity in the monocyte cluster. G CITE-Seq QC metric ‘Number of Detected Antibodies per Cell’ split by individual donors

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BMC Bioinformatics

ISSN: 1471-2105

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