Garth Kong1, Thai Nguyen2, Wesley Rosales2, Anjali Panikar2, John Cheney2, Brittany Curtiss1, Sarah Carratt1, Theodore Braun1, Julia Maxson1
1 Oregon Health and Science University, Division of Oncological Sciences
2 University of Oregon, Knight Cancer Internship Program - Bioinformatics
Multi-omic single-cell sequencing assays measure multiple macromolecules 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 dimensions of data in these assays can be leveraged to better identify cell clusters - an essential step for downstream analyses and interpretation. 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. In this workshop, we will go over all the features of CITEViz.
BioConductor workshops are available as Docker containers before and after the conference. To access the CITEViz workshop contents, make sure you have Docker installed, and then use the following instructions in a terminal:
docker run -e PASSWORD=abc -p 8787:8787 ghcr.io/gartician/citevizworkshop:latestAnd then input localhost:8787 into your local web browser and sign in using rstudio as the username and the value of PASSWORD as the password. Then input the following into the R console:
CITEViz is also available for installation using devtools in R. In your local RStudio environment, use the following code:
devtools::install_github("maxsonBraunLab/CITE-Viz")
library(CITEViz)
run_app()CITEViz is a short workshop within the BioConductor 2022 conference and it comes with accompanying slides located here.