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
··· 4 4 <div style="backgroud-color: #f5f5f5; padding: 10px"> 5 5 library(scImmuCC) 6 6 7 - data(package="scImmuCC) 8 - data(test_data,package="scImmuCC") # load the test data 7 + data(package="scImmuCC) 8 + data(test_data,package="scImmuCC") # load the test data 9 9 10 - count <- as.matrix(test_data) # Convert test data to matrix 10 + count <- as.matrix(test_data) # Convert test data to matrix 11 11 12 - test <- scImmuCC_Layered(count = count ,Non_Immune = FALSE) 12 + test <- scImmuCC_Layered(count = count ,Non_Immune = FALSE) 13 13 14 14 </div> 15 15 ··· 29 29 library(scImmuCC) 30 30 31 31 count <- read.csv(file=filename) #read your scRNA-Seq file 32 - dim(count) 32 + 33 33 count <- as.matrix(count) 34 + 34 35 test <- scImmuCC_Layered(test_data,Non_Immune=FALSE) #if your data have non-immune cell, Nn_Immune = TRUE 35 36 36 37 The annotation results will be output in your current running directory。