CITEViz

CITEViz performs interactive gating and quality-control analyses of CITE-Seq datasets, classifying single-cell populations by surface protein expression and integrating with Seurat-processed single-cell RNA data in an R-Shiny implementation.

Key Features:

• Interactive Gating Workflow: Performs flow cytometry-like gating within R-Shiny to classify populations such as CD14 monocytes, CD4 T cells, CD8 T cells, NK cells, B cells, and platelets using canonical surface protein markers.
• Integration with Seurat-Processed Data: Operates on CITE-Seq data processed by Seurat, preserving compatibility with Seurat data structures.
• Quality Control Visualization: Provides visualization of basic quality-control metrics and generates QC figures and feature plots for multi-omic datasets.
• Investigation of Cellular Heterogeneity: Enables analysis of cellular heterogeneity including CD14- and CD16-expressing monocyte subsets and detection of donor-level variation such as differential numbers of detected antibodies per patient donor.

Scientific Applications:

• Cell Population Classification: Classifies single-cell populations in CITE-Seq datasets based on surface protein expression gating.
• Multi-omic Integration: Supports combined analysis of RNA transcriptome profiling and surface protein expression from Seurat-processed data.
• Quality Assessment: Facilitates dataset integrity assessment through QC metric visualization and QC figure generation.
• Heterogeneity and Donor Variation Analysis: Enables investigation of cellular heterogeneity such as CD14/CD16 monocyte diversity and donor-level differences in detected antibodies.

Methodology:

Implemented as an R-Shiny application that performs interactive, flow cytometry-like gating on CITE-Seq data processed by Seurat and produces QC visualizations and feature plots.