Hierarchical annotation of immune cells in scRNA-Seq data based on ssGSEA algorithm. Fork for large datasets with QOL improvements.

Update seurat_maps.R

authored by Yingjiang17 and committed by GitHub fc007bde 88724f37

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R
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R/seurat_maps.R
··· 15 15 seurat_Heatmap <- function(count,genematrix,ssGSEA_result,filename){ 16 16 17 17 count <- count[, !duplicated(colnames(count))] 18 + celltype <- intersect(colnames(count),ssGSEA_result[,1]) 19 + labels <- ssGSEA_result[which(ssGSEA_result[,1]%in%celltype),] 20 + count <- count[,labels[,1]] 21 + 18 22 seurat.data <- CreateSeuratObject(counts = count, project = filename)#, min.cells = 3, min.features = 200) 19 23 seurat.data 20 24 seurat.data[["percent.mt"]] <- PercentageFeatureSet(seurat.data, pattern = "^MT-") ··· 59 63 head(seurat.data@reductions$tsne@cell.embeddings) 60 64 61 65 #Add annotation information to Seurat object 62 - seurat.data@meta.data$cell_type_pred <- ssGSEA_result[,2] 66 + seurat.data@meta.data$cell_type_pred <-labels[,2] 63 67 64 68 pdf(paste(filename, "_tSNE", ".pdf", sep=""), width=12, height=10) 65 69 p1 <- DimPlot(seurat.data, reduction = "tsne", group.by = "cell_type_pred",label = TRUE, pt.size=1)