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install.packages("ape")
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RV_Infected<-RV_infected_mock_intergreted[,RV_infected_mock_intergreted$sample%in%"RV_infected"]
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RV_MOCK<-RV_infected_mock_intergreted[,RV_infected_mock_intergreted$sample%in%"MOCK"]
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rAAV_Infected<-all.Adult[,all.Adult$BC_label%in%"Barcoded"]
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rAAV_MOCK<-all.Adult[,all.Adult$BC_label%in%"Unbarcoded"]
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VIRUS_LIST<-list(RV_Infected,RV_MOCK,rAAV_Infected,rAAV_MOCK)
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virus_sample_name<- c('RV_infected', 'RV_MOCK',"rAAV_infected","rAAV_MOCK")
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for (i in 1:length(VIRUS_LIST)){
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VIRUS_LIST[[i]]@meta.data$sample <- virus_sample_name[[i]]}
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p <- list()
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for (i in 1:4){
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p[[i]] <- DimPlot(VIRUS_LIST[[i]], reduction = 'tsne') +
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labs(title = virus_sample_name[i]) +
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guides(colour=guide_legend(ncol=2, override.aes = list(size=2)))
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}
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plot_grid(plotlist = p, ncol =2)
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features <- SelectIntegrationFeatures(object.list = VIRUS_LIST)
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adult.anchors <- FindIntegrationAnchors(object.list = VIRUS_LIST,
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anchor.features = features)
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adult.inte <- IntegrateData(anchorset = adult.anchors)
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adult.inte <- ScaleData(adult.inte, verbose = FALSE)
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adult.inte <- RunPCA(adult.inte, npcs = 10, verbose = FALSE)
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adult.inte <- FindNeighbors(adult.inte, reduction = "pca", dims = 1:20)
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adult.inte <- FindClusters(adult.inte, resolution = 1)
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adult.inte <- RunUMAP(adult.inte, reduction = "pca", dims = 1:10)
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adult.inte <- RunTSNE(adult.inte, reduction = "pca", dims = 1:10)
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adult.inte$seurat_clusters
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VlnPlot(adult.inte,
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features = c("Snap25",'Gad1','Gad2',"Sox6",
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"Pvalb","Sst","Prox1","Vip",
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"Aldoc", "Slc1a3", "Aqp4", "Olig2", "Olig1","Pdgfra", "C1ql1","Fcrls", "Trem2",
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"Slc17a7",'Calb1','Cux2','Rorb','Bdnf',
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'Ptn',"Col23a1",
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'Tshz2','Cbln2','Grp',"Syt6",
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'Pou3f1','Etv1','Adamts2','Dlk1','Npr3'),
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stack = TRUE, flip = TRUE, assay = 'RNA') + NoLegend()
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level_maintype<-c( "Pvalb","Sst","Vip/Lamp5","Astro","Oligo","Microglia","L2/3IT","L4/5IT","L6IT","L5NP","L6CT","L5ET")
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Idents(adult.inte) <- factor(Idents(adult.inte),levels=level_maintype)
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levels(Idents(adult.inte))
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Idents(adult.inte) <- 'seurat_clusters'
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Idents(adult.inte) <- 'Maintype'
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adult.inte<- BuildClusterTree(object = adult.inte, dims=1:10)
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phy <- Tool(object = adult.inte, slot = 'BuildClusterTree')
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plot(phy)
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adult.inte$Maintype <- as.character(adult.inte$seurat_clusters)
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adult.inte$Maintype[which(adult.inte$Maintype %in% c(8))] <- "Pvalb"
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adult.inte$Maintype[which(adult.inte$Maintype %in% c(9))] <- "Sst"
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adult.inte$Maintype[which(adult.inte$Maintype %in% c(13,27))] <- "Vip/Lamp5"
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adult.inte$Maintype[which(adult.inte$Maintype %in% c(2,14))] <- "L2/3IT"
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adult.inte$Maintype[which(adult.inte$Maintype %in% c(0,6))] <- "L4/5IT"
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adult.inte$Maintype[which(adult.inte$Maintype %in% c(3,4,23,25,19))] <- "L6IT"
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adult.inte$Maintype[which(adult.inte$Maintype %in% c(1))] <- "L6CT"
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adult.inte$Maintype[which(adult.inte$Maintype %in% c(11))] <- "L5ET"
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adult.inte$Maintype[which(adult.inte$Maintype %in% c(16))] <- "L5NP"
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adult.inte$Maintype[which(adult.inte$Maintype %in% c(10,15,21))] <- "Microglia"
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adult.inte$Maintype[which(adult.inte$Maintype %in% c(5,17,24,7))] <- "Astro"
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adult.inte$Maintype[which(adult.inte$Maintype %in% c(12,18,20,22,26))] <- "Oligo"
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adult.inte$Maintype[which(adult.inte$Maintype %in% c(7))] <- "7"
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adult.inte$Maintype[which(adult.inte$Maintype %in% c(19))] <- "19"
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Idents(adult.inte) <- 'Maintype'
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VlnPlot(adult.inte,
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features = c('Gad1',"Sox6","Pvalb","Sst","Prox1","Vip","Lamp5","Slc17a7","Col23a1",
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"Rorb","Foxp2","Bcl6","Ctss","Slc1a3","Mog"),group.by = "Maintype",stack = TRUE, flip = TRUE, fill.by="ident", assay = 'RNA') +
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NoLegend()
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DimPlot(adult.inte, reduction = 'umap', label = T, ncol = 2)
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DimPlot(adult.inte, split.by = 'sample', reduction = 'tsne', label = T, ncol = 2) +
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theme(axis.line = element_blank(), axis.ticks = element_blank(),
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axis.text = element_blank(), plot.title = element_text(size = 30)) +
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labs(x='', y='')
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saveRDS(adult.inte,"H:/Project1_RV Receptor Projection/FIG1.鐨眰鍗曠粏鑳濺V rAAV鎰熸煋鏁版嵁鍒嗘瀽/rAAV_RV.inte2.RDS")
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table(SLQ_IPC$predicted.id)
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SLQ_IPC$`ACB-I`
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SLQ_IPC$`BLA-I` |
