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STvEA

STvEA is an analysis pipeline for cleaning, clustering, and plotting CODEX and CITE-seq protein data, mapping a CODEX dataset to a matching CITE-seq dataset, and assessing colocalization of features using the Adjacency Score. More information can be found in:

K. W. Govek*, E. C. Troisi*, Z. Miao, R. G. Aubin, S. Woodhouse, and P. G. Cámara. Single-Cell Transcriptomic Analysis of mIHC Images via Antigen Mapping. Science Advances 7 (2021) 10. DOI: 10.1126/sciadv.abc5464. *authors contributed equally.

Installation

Install flowCore

# Bioconductor 3.6 (R 3.4)
source("https://bioconductor.org/biocLite.R")
biocLite("flowCore")

------ or ------

# Bioconductor 3.8+ (R 3.5+)
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("flowCore")

Install STvEA

devtools::install_github("CamaraLab/STvEA")

Docker image

We provide Docker images to run STvEA in R Studio, based off the rocker/rstudio images: https://hub.docker.com/r/camaralab/stvea

Tutorials

Analyzing CODEX data

Example pipeline for only CODEX data. Performs filtering of protein expression data, visualization of clusters, and analysis of the spatial co-localization of both clusters and proteins.

Analyzing CyTOF data and reading from FCS files

Example pipeline for reading CyTOF or CODEX data from FCS files and analyzing mIHC or cytometry data without a spatial component.

Mapping CODEX data to CITE-seq data

Performs separate filtering and clustering for both CODEX and CITE-seq protein expression data. Maps the CODEX protein space to the CITE-seq protein space in order to transfer features such as gene expression and clusters from the CITE-seq cells onto the CODEX cells. Analyzes co-localization of genes, proteins, and clusters using the Adjacency Score.

Mapping CODEX data to CITE-seq data analyzed using Seurat

Retrieves information about the CITE-seq mRNA and protein expression data from a Seurat object. Performs separate filtering and clustering for both CODEX and CITE-seq protein expression data. Maps the CODEX protein space to the CITE-seq protein space in order to transfer features such as gene expression and clusters from the CITE-seq cells onto the CODEX cells. Analyzes co-localization of genes, proteins, and clusters using the Adjacency Score.