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
··· 2 2 3 3 The below demonstrates the result of Hierarchical annotation for some immune cells in the E-MTAB-11536 dataset (included in the package) 4 4 <div style="backgroud-color: #f5f5f5; padding: 10px"> 5 - library(scImmuCC) 5 + library(scImmuCC) 6 6 7 7 data(package="scImmuCC) 8 8 data(test_data,package="scImmuCC") # load the test data ··· 28 28 The following is a quick tutorial on how to use scImmuCC to annotate immune cell types in scRNA-Seq. 29 29 <div style="backgroud-color: #f5f5f5; padding: 10px"> 30 30 library(scImmuCC) 31 - count <- read.csv(file=filename) #read your scRNA-Seq file 32 - count <- as.matrix(count) 31 + count <- read.csv(file=filename) ##read your scRNA-Seq file 32 + count <- as.matrix(count) 33 33 test <- scImmuCC_Layered(test_data,Non_Immune=FALSE) 34 - #if your data have non-immune cell, Nn_Immune = TRUE 34 + ##if your data have non-immune cell, Nn_Immune = TRUE 35 35 </div> 36 36 The annotation results will be output in your current running directory。 37 37