--- a
+++ b/RNA-seq/AnalysisPipeline/NK.analysis.R
@@ -0,0 +1,37 @@
+#' @description: analysis NK cell population
+
+library(Seurat)
+library(harmony)
+library(clustree)
+library(ggpubr)
+library(dplyr)
+library(tidyverse)
+library(patchwork)
+library(ComplexHeatmap)
+library(circlize)
+library(vegan)
+library(openxlsx)
+set.seed(101)
+library(future)
+plan("multiprocess", workers = 5) 
+options(future.globals.maxSize = 50000 * 1024^2) # set 50G RAM
+set.resolutions <- seq(0.1, 0.8, by = 0.1)
+
+setwd(dir = "/data/active_data/lzl/RenalTumor-20200713/DataAnalysis-20210803/scRNA")
+data.merge <- readRDS("data.merge.pro.rds")
+
+#### observate the marker expression
+NK.markers <- c("CD3D", "CD8A", "KLRD1", "GNLY")
+pdf("2.Cluster/AnnotateCellType/NK.marker.pdf")
+FeaturePlot(data.merge, features = NK.markers, cols = c("lightgrey", "red"), ncol = 2)
+dev.off()
+
+cell.Type <- "NK/NKT cell"
+sub.scRNA <- subset(data.merge, subset = cellType_low == cell.Type)
+#### plot the sub-NK plot
+cell.locations <- as.data.frame(sub.scRNA@reductions$umap@cell.embeddings)
+cells <- rownames(cell.locations)[which(cell.locations$UMAP_1 < -4 & cell.locations$UMAP_2 > 0)]
+sub.scRNA.NK <- subset(sub.scRNA, cells = cells)
+pdf("2.Cluster/AnnotateCellType/NK.marker.pdf")
+FeaturePlot(sub.scRNA.NK, features = NK.markers, cols = c("lightgrey", "red"), ncol = 2)
+dev.off()