byarielm.fyi / scImmuCC
Hierarchical annotation of immune cells in scRNA-Seq data based on ssGSEA algorithm. Fork for large datasets with QOL improvements.
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README.md

sc-ImmuCC: Hierarchical annotation for immune cell types in single-cell RNA-Seq#

Installation#

R programming language >= 4.1.1 ，packages Seurat and GSVA are required to use scImmuCC.

The installation from GitHub is in experimental stage but gives the newest feature:

if (!requireNamespace("Seurat", quietly = TRUE))
    install.packages("Seurat")

if (!requireNamespace("GSVA", quietly = TRUE))
    BiocManager::install("GSVA")

if (!requireNamespace("remotes", quietly = TRUE))
    install.packages("remotes")

remotes::install_github("wuaipinglab/scImmuCC")

Example#

Below is an example of Hierarchical annotation for some immune cells in the E-MTAB-11536 dataset (included in the package)

library(scImmuCC) 
data(package="scImmuCC)
data(test_data,package="scImmuCC") # load the test data

count <- as.matrix(test_data) # Convert test data to matrix

test <- scImmuCC_Layered(count = count ,Non_Immune = FALSE)

QuickStart#

The following is a quick tutorial on how to use scImmuCC to annotate immune cell types in scRNA-Seq.

library(scImmuCC)

count <- read.csv(file=filename)     ##read your scRNA-Seq file
         
count <- as.matrix(count)

test <- scImmuCC_Layered(test_data,Non_Immune=FALSE)    ##if your data have non-immune cell, Nn_Immune = TRUE
The annotation results will be output in your current running directory。