Seurat对象

1. 查看seurat对象的结构: str(object)
2. seurat对象的元信息: object@meta.data
3. 指定使用的idents: Idents(object) <- "seurat_clusters"
4. 指定使用的assay: DefaultAssay(object) <- "SCT"

获取基因

rownames(object)

获取细胞

1. 全部细胞: colnames(object) / Cells(object) / rownames(object@meta.data)
2. 指定细胞:

• rownames(object@meta.data)[which(object@meta.data$seurat_clusters %in% clusters)]
• WhichCells(object, idents = c(1, 2, 3)) / WhichCells(object, expression = gene > 0, slot = "counts")

获取Seurat子集

1. subset(object, cells = cells)
2. subset(object, idents = c(1, 2, 3)) (取反: invert = TRUE)
3. subset(object, gene > 0, slot = "counts")
4. object[, object@meta.data$seurat_clusters %in% clusters]

获取表达信息

1. FetchData(object, c(genetable$gene, "clustertype", "majortype"))
2. GetAssayData(object, assay = 'RNA', slot = "counts")
3. as.matrix(object@assays$RNA@counts)

获取降维坐标信息

Embeddings(object = object[["umap"]])

细胞identity

1. 获取identity: Idents(object)
2. 根据细胞设置identity: Idents(object, cells = cells) <- 'Astrocyte'
3. 修改idents名字: RenameIdents(object, '0' = 'A', '1' = 'B')
4. 设置细胞identity: SetIdent(object, cells = cells, value = 'A') StashIdent(object, save.name = 'idents') (将细胞identity添加到元信息)

计算细胞数目/比例

1. 总细胞数: nrow(object@meta.data)
2. 每个群细胞数目: table(Idents(object)) / table(object$RNA_snn_res.0.8)
3. 每个群细胞比例: prop.table(table(Idents(object))) / prop.table(table(object$RNA_snn_res.0.8))