Reference

install.packages("devtools")
library(devtools)
install_github("LTLA/SingleR")

install.packages("remotes")
remotes::install_github("LTLA/celldex")

library(SingleR)
library(celldex)
ref <- HumanPrimaryCellAtlasData() 
ref <- HumanPrimaryCellAtlasData() 
save(ref,file = 'HumanPrimaryCellAtlasData.Rdata')
ref <- BlueprintEncodeData() 
save(ref,file = 'BlueprintEncodeData.Rdata')
ref <- MouseRNAseqData() 
save(ref,file = 'MouseRNAseqData.Rdata')
ref <- ImmGenData() 
save(ref,file = 'ImmGenData.Rdata')
ref <- DatabaseImmuneCellExpressionData() 
save(ref,file = 'DatabaseImmuneCellExpressionData.Rdata')
ref <- NovershternHematopoieticData() 
save(ref,file = 'NovershternHematopoieticData.Rdata')
ref <- MonacoImmuneData()
save(ref,file = 'MonacoImmuneData.Rdata')

load("../ref/MonacoImmuneData.Rdata")
ls()
head(ref$label.main)

data_for_SingleR <- GetAssayData(SeuratObj, layer="scale.data")
clusters <- SeuratObj@meta.data$seurat_cluster
predicted_id <- SingleR(test = data_for_SingleR, 
                        ref = ref, 
                        labels = ref$label.main,
                        clusters = clusters)
predicted_id 

write.csv(predicted_id,"output/predicted_id_MonacoImmuneData.csv",quote = F,row.names = F)


cellType=data.frame(ClusterID=levels(SeuratObj@meta.data$seurat_clusters),
                    SingleR_MonacoImmune=predicted_id$labels)

# ADD Predicted id to my SeuratObjecct
SeuratObj@meta.data$SingleR_MonacoImmune <- cellType[match(clusters,cellType$ClusterID),'SingleR_MonacoImmune']

DimPlot(SeuratObj,reduction = "umap.harmony",group.by = "singleR",label=T)
ggsave(file="output/cell_anno/SingleR_MonacoImmune_umap.pdf")

predicted_id