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CITE-Viz: Replicating the Interactive Flow Cytometry Workflow in CITE-Seq

Kong, G. L.; Nguyen, T. T.; Rosales, W. K.; Panikar, A. D.; Cheney, J. H. W.; Curtiss, B. M.; Carratt, S. A.; Braun, T. P.; Maxson, J. E.

2022-05-16 bioinformatics
10.1101/2022.05.15.491411 bioRxiv
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SummaryThe rapid advancement of new genomic sequencing technology has enabled the development of multi-omic single-cell sequencing assays. These assays profile multiple modalities in the same cell and can often yield new insights not revealed with a single modality. For example, CITE-Seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing) simultaneously profiles the single-cell RNA transcriptome and the surface protein expression. The extra dimension of surface protein markers can be used to further identify cell clusters - an essential step for downstream analyses and interpretation. Additionally, multi-dimensional datasets like CITE-Seq require nuanced visualization methods to accurately assess the data. To facilitate cell cluster classification and visualization in CITE-Seq, we developed CITE-Viz. CITE-Viz is a single-cell visualization platform with a custom module that replicates the interactive flow-cytometry gating workflow. With CITE-Viz, users can investigate CITE-Seq specific quality control (QC) metrics, view multi-omic co-expression feature plots, and classify cell clusters by iteratively gating on the abundance of cell surface markers. CITE-Viz was developed to make multi-modal single-cell analysis accessible to a wide variety of biologists, with the aim to discover new insights into their data and to facilitate novel hypothesis generation. Availability and ImplementationCITE-Viz installation and usage instructions can be found in the GitHub repository https://github.com/maxsonBraunLab/CITE-Viz Contactmaxsonj@ohsu.edu Supplementary InformationDown-sampled peripheral blood mononuclear dataset (Hao et al. 2021): https://bit.ly/3vxbhfW

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