在cluster ID 和replicate之间切换身份类型 代码语言:javascript 代码运行次数:0 复制Cloud Studio 代码运行 # Plot UMAP, coloring cells by cell type (currently stored in object@ident) DimPlot(pbmc, reduction = "umap") 代码语言:javascript 代码运行次数:0 复制Cloud Studio 代码运行 # How do I create...
Human <- xseurat2::human_celldex_BlueprintEncodeData #预测细胞类型1,使用method = "cluster"方法,聚在同一类的细胞都会注释成一种细胞类型 Anno1 <- SingleR(test = data_for_SingleR, ref = Human, labels = Human$label.main, method = "cluster", clusters = pbmc@meta.data$seurat_clusters) #把...
# step 12 Finding differentially expressed features (cluster biomarkers) # find all markers of cluster 2 #cluster2.markers <- FindMarkers(pbmc, ident.1 = 2, min.pct = 0.25) #head(cluster2.markers, n = 5) # find all markers distinguishing cluster 5 from clusters 0 and 3 #cluster5.mark...
#' #' @param object Seurat object #' @param dims Dimensions to plot, must be a two-length numeric vector specifying x- and y-dimensions 长度为2的向量,指定x和y轴。 #' @param cells Vector of cells to plot (default is all cells) #' @param cols Vector of colors, each color correspon...
To visualize the two conditions side-by-side, we can use the split.by argument to show each condition colored by cluster. 代码语言:txt 复制 DimPlot(immune.combined, reduction = "umap", split.by = "stim") Identify conserved cell type markers ...
# How can I extract expression matrix for all NK cells (perhaps, to load into another package)nk.raw.data<-as.matrix(GetAssayData(pbmc,slot="counts")[,WhichCells(pbmc,ident="NK")])# Can I create a Seurat object based on expression of a feature or value in object metadata?subset(pbmc...
# Switch back to cell type labels Idents(pbmc) <- "CellType" 其实我们不转换ident大部分的绘图也可以用group.by来指定分群方式 DimPlot(pbmc,reduction="umap",group.by="replicate") 统计分群信息 # How many cells are in each cluster table(Idents(pbmc)) ...
#预测细胞类型1,使用method = "cluster"方法,聚在同一类的细胞都会注释成一种细胞类型 Anno1 <- SingleR(test = data_for_SingleR, ref = Human, labels = Human$label.main, method = "cluster", clusters = pbmc@meta.data$seurat_clusters)
As you kindly made the Seurat object for me, there are already tSNE and cluster information provided by Nature medicine paper which you added that to the metadata here How I can use tSNE information from the metadata instead of demential reduction by myself? Collaborator samuel-marsh commented...
theme(legend.position="none")+ ggtitle("identities on x-axis")# Use patchwork to join plotsa+b Withggplot2 Given adata.frameand a vector of identity classes (cluster ID), a stacked violin plot can be created with theggplot2package. ...