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
··· 1 1 # sc-ImmuCC: Hierarchical annotation for immune cell types in single-cell RNA-Seq 2 2 3 - The below demonstrates the result of Hierarchical annotation for some immune cells in the E-MTAB-11536 dataset (included in the package) 4 - <div style="backgroud-color: #f5f5f5; padding: 10px"> 5 - library(scImmuCC) 6 - 7 - data(package="scImmuCC) 8 - data(test_data,package="scImmuCC") # load the test data 9 - 10 - count <- as.matrix(test_data) # Convert test data to matrix 11 - 12 - test <- scImmuCC_Layered(count = count ,Non_Immune = FALSE) 13 - 14 - </div> 15 3 16 4 # Installation 17 5 R programming language >= 4.1.1 ,packages Seurat and GSVA are required to use scImmuCC. ··· 31 19 remotes::install_github("wuaipinglab/scImmuCC") 32 20 </div> 33 21 22 + # Example 23 + Below is an example of Hierarchical annotation for some immune cells in the E-MTAB-11536 dataset (included in the package) 24 + 25 + <div style="backgroud-color: #f5f5f5; padding: 10px"> 26 + library(scImmuCC) 27 + 28 + data(package="scImmuCC) 29 + data(test_data,package="scImmuCC") # load the test data 30 + 31 + count <- as.matrix(test_data) # Convert test data to matrix 32 + 33 + test <- scImmuCC_Layered(count = count ,Non_Immune = FALSE) 34 + 35 + </div> 36 + 37 + 34 38 # QuickStart 35 39 The following is a quick tutorial on how to use scImmuCC to annotate immune cell types in scRNA-Seq. 40 + 36 41 <div style="backgroud-color: #f5f5f5; padding: 10px"> 37 42 38 43 library(scImmuCC)