Fix labels

r.scripts/sc-TissueMapper_ID.R

@@ -82,6 +82,7 @@ rm(common)
 
 singler <- SingleR(sc10x.se,ref=list(lung.P1=lin.P1,lung.P2=lin.P2,lung.P3=lin.P3),method="single",labels=list(lung.P1=lin.P1$label.fine,lung.P2=lin.P2$label.fine,lung.P3=lin.P3$label.fine),de.method="wilcox",BPPARAM=BiocParallel::MulticoreParam(workers=20))
 sc10x$pop <- singler$labels
+labs.raw <- singler$labels
 labs <- singler$labels
 labs[labs %in% c("Differentiating Basal","Proliferating Basal","Basal","Mesothelial","Alveolar Epithelial Type 2","Club","Alveolar Epithelial Type 1","Ciliated","Signaling Alveolar Epithelial Type 2","Proximal Basal","Neuroendocrine","Mucous","Ionocyte","Serous","Proximal Ciliated","Goblet")] <- "Epithelia"
 labs[labs %in% c("Adventitial Fibroblast","Alveolar Fibroblast","Lipofibroblast")] <- "Fibroblast"
@@ -91,6 +92,7 @@ labs[labs %in% c("CD4+ Memory/Effector T","CD4+ Naive T","CD8+ Memory/Effector T
 labs[labs %in% c("Classical Monocyte","Nonclassical Monocyte","Myeloid Dendritic Type 2","IGSF21+ Dendritic","EREG+ Dendritic","Myeloid Dendritic Type 1","TREM2+ Dendritic","Macrophage","Proliferating Macrophage")] <- "Myeloid"
 labs[labs %in% c("Basophil/Mast 1","Basophil/Mast 2")] <- "Granulocyte"
 sc10x$lin <- labs
+sc10x$lung <- labs.raw
 #DimPlot(sc10x,group.by="lin",reduction="umap",label=TRUE,repel=TRUE)+theme(legend.position="none")
 
 Idents(sc10x) <- "lin"
@@ -184,6 +186,8 @@ if (opt$o == "pr" && opt$s == "hu") {
   #DimPlot(sc10x.epi,group.by="pop",reduction="umap",label=TRUE,repel=TRUE)+theme(legend.position="none")
 } else if (opt$o == "pr" && opt$s == "mu") {
   sc10x.epi$pop <- sc10x.epi$lin
+} else {
+  sc10x.epi$pop <- sc10x.epi$lin
 }
 
 sc10x$pop <- sc10x$lin
@@ -220,12 +224,12 @@ DefaultAssay(object=sc10x.fmst) <- "SCT"
 DefaultAssay(object=sc10x.fib) <- "SCT"
 DefaultAssay(object=sc10x.sm) <- "SCT"
 DefaultAssay(object=sc10x.leu) <- "SCT"
-sc10x@meta.data <- sc10x@meta.data[,c("lin","pop","samples","integrated_snn_res.0.1","integrated_snn_res.0.2","integrated_snn_res.0.3","integrated_snn_res.0.4","integrated_snn_res.0.5","integrated_snn_res.0.75","integrated_snn_res.1","integrated_snn_res.2","integrated_snn_res.3","integrated_snn_res.4","integrated_snn_res.5","nCount_RNA","nFeature_RNA","percent.mito","percent.ribo","Stress1")]
-sc10x.epi@meta.data <- sc10x.epi@meta.data[,c("lin","pop","samples","integrated_snn_res.0.1","integrated_snn_res.0.2","integrated_snn_res.0.3","integrated_snn_res.0.4","integrated_snn_res.0.5","integrated_snn_res.0.75","integrated_snn_res.1","integrated_snn_res.2","integrated_snn_res.3","integrated_snn_res.4","integrated_snn_res.5","nCount_RNA","nFeature_RNA","percent.mito","percent.ribo","Stress1")]
-sc10x.fmst@meta.data <- sc10x.fmst@meta.data[,c("lin","samples","integrated_snn_res.0.1","integrated_snn_res.0.2","integrated_snn_res.0.3","integrated_snn_res.0.4","integrated_snn_res.0.5","integrated_snn_res.0.75","integrated_snn_res.1","integrated_snn_res.2","integrated_snn_res.3","integrated_snn_res.4","integrated_snn_res.5","nCount_RNA","nFeature_RNA","percent.mito","percent.ribo","Stress1")]
-sc10x.fib@meta.data <- sc10x.fib@meta.data[,c("lin","samples","integrated_snn_res.0.1","integrated_snn_res.0.2","integrated_snn_res.0.3","integrated_snn_res.0.4","integrated_snn_res.0.5","integrated_snn_res.0.75","integrated_snn_res.1","integrated_snn_res.2","integrated_snn_res.3","integrated_snn_res.4","integrated_snn_res.5","nCount_RNA","nFeature_RNA","percent.mito","percent.ribo","Stress1")]
-sc10x.sm@meta.data <- sc10x.sm@meta.data[,c("lin","samples","integrated_snn_res.0.1","integrated_snn_res.0.2","integrated_snn_res.0.3","integrated_snn_res.0.4","integrated_snn_res.0.5","integrated_snn_res.0.75","integrated_snn_res.1","integrated_snn_res.2","integrated_snn_res.3","integrated_snn_res.4","integrated_snn_res.5","nCount_RNA","nFeature_RNA","percent.mito","percent.ribo","Stress1")]
-sc10x.leu@meta.data <- sc10x.leu@meta.data[,c("lin","pop","samples","integrated_snn_res.0.1","integrated_snn_res.0.2","integrated_snn_res.0.3","integrated_snn_res.0.4","integrated_snn_res.0.5","integrated_snn_res.0.75","integrated_snn_res.1","integrated_snn_res.2","integrated_snn_res.3","integrated_snn_res.4","integrated_snn_res.5","nCount_RNA","nFeature_RNA","percent.mito","percent.ribo","Stress1")]
+sc10x@meta.data <- sc10x@meta.data[,c("lin","pop","lung","samples","integrated_snn_res.0.1","integrated_snn_res.0.2","integrated_snn_res.0.3","integrated_snn_res.0.4","integrated_snn_res.0.5","integrated_snn_res.0.75","integrated_snn_res.1","integrated_snn_res.2","integrated_snn_res.3","integrated_snn_res.4","integrated_snn_res.5","nCount_RNA","nFeature_RNA","percent.mito","percent.ribo","Stress1")]
+sc10x.epi@meta.data <- sc10x.epi@meta.data[,c("lin","pop","lung","samples","integrated_snn_res.0.1","integrated_snn_res.0.2","integrated_snn_res.0.3","integrated_snn_res.0.4","integrated_snn_res.0.5","integrated_snn_res.0.75","integrated_snn_res.1","integrated_snn_res.2","integrated_snn_res.3","integrated_snn_res.4","integrated_snn_res.5","nCount_RNA","nFeature_RNA","percent.mito","percent.ribo","Stress1")]
+sc10x.fmst@meta.data <- sc10x.fmst@meta.data[,c("lin","lung","samples","integrated_snn_res.0.1","integrated_snn_res.0.2","integrated_snn_res.0.3","integrated_snn_res.0.4","integrated_snn_res.0.5","integrated_snn_res.0.75","integrated_snn_res.1","integrated_snn_res.2","integrated_snn_res.3","integrated_snn_res.4","integrated_snn_res.5","nCount_RNA","nFeature_RNA","percent.mito","percent.ribo","Stress1")]
+sc10x.fib@meta.data <- sc10x.fib@meta.data[,c("lin","lung","samples","integrated_snn_res.0.1","integrated_snn_res.0.2","integrated_snn_res.0.3","integrated_snn_res.0.4","integrated_snn_res.0.5","integrated_snn_res.0.75","integrated_snn_res.1","integrated_snn_res.2","integrated_snn_res.3","integrated_snn_res.4","integrated_snn_res.5","nCount_RNA","nFeature_RNA","percent.mito","percent.ribo","Stress1")]
+sc10x.sm@meta.data <- sc10x.sm@meta.data[,c("lin","lung","samples","integrated_snn_res.0.1","integrated_snn_res.0.2","integrated_snn_res.0.3","integrated_snn_res.0.4","integrated_snn_res.0.5","integrated_snn_res.0.75","integrated_snn_res.1","integrated_snn_res.2","integrated_snn_res.3","integrated_snn_res.4","integrated_snn_res.5","nCount_RNA","nFeature_RNA","percent.mito","percent.ribo","Stress1")]
+sc10x.leu@meta.data <- sc10x.leu@meta.data[,c("lin","lung","pop","samples","integrated_snn_res.0.1","integrated_snn_res.0.2","integrated_snn_res.0.3","integrated_snn_res.0.4","integrated_snn_res.0.5","integrated_snn_res.0.75","integrated_snn_res.1","integrated_snn_res.2","integrated_snn_res.3","integrated_snn_res.4","integrated_snn_res.5","nCount_RNA","nFeature_RNA","percent.mito","percent.ribo","Stress1")]
 saveRDS(sc10x,paste0("./analysis/",opt$p,"_id_all.rds"))
 saveRDS(sc10x.epi,paste0("./analysis/",opt$p,"_id_epi.rds"))
 saveRDS(sc10x.fmst,paste0("./analysis/",opt$p,"_id_fmst.rds"))