CITEViz: CITEViz: CITEViz: Classifying Cell Clusters in CITE-Seq Data...

In maxsonBraunLab/CITE-Viz: "CITEViz: Classifying Cell Clusters in CITE-Seq Data using the Flow Cytometry Gating Workflow"

CITEViz: CITEViz: Classifying Cell Clusters in CITE-Seq Data using the Flow Cytometry Gating Workflow

Description

CITEViz CITEViz is an RShiny app that allows users to classify cell types in CITE-Seq data via cellular surface protein levels. Similar to flow cytometry, users can physically draw gates and filter on a mixture of cells, and the selected cells are immediately highlighted in dimensional reduction space (e.g. UMAP, tSNE, PCA). This workflow provides rapid feedback to the users to help classify cell types. To read more about CITEViz, click (here. https://github.com/maxsonBraunLab/CITEViz)

Details

The input of CITEViz is a pre-processed Seurat/SingleCelExperiment object with assays containing normalized RNA/SCT (single-cell transform) and ADT (antibody-derived tag) count data, as well as data for at least one dimensional reduction (e.g. UMAP, PCA, etc.). The CITEViz package allows users to quickly download an example dataset for the CITEViz tutorial.

Example data can be found in the (CITEVizTestData ExperimentHub https://github.com/maxsonBraunLab/CITEVizTestData) link. The dataset is a CITE-Seq assay of human peripheral bone and mononuclear cells with 2500 cells and 228 antibodies from (Hao et. al. 2021, https://linkinghub.elsevier.com/retrieve/pii/S0092-8674(21)00583-3) made available through the (Creative Commons BY 4.0, https://creativecommons.org/licenses/by/4.0/) license.

Author(s)

Garth Kong [e-mail]

Thai Nguyen [e-mail]

Wesley Rosales [e-mail]

Anjali Panikar [e-mail]

John Cheney [e-mail]

maxsonBraunLab/CITE-Viz documentation built on Oct. 26, 2023, 9:52 p.m.