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在此，我们将合并两个 10X PBMC 数据集：一个包含 4K 细胞，一个包含 8K 细胞。数据集可以在这里[1]找到。 首先，我们在数据中读入并创建两个Seurat对象。 library(Seurat)
pbmc4k.data <- Read10X(data.dir = "../data/pbmc4k/filtered_gene_bc_matrices/GRCh38/")
pbmc4k <- CreateSeuratObject(counts = pbmc4k.data, project = "PBMC4K")
pbmc4k
## An object of class Seurat
## 33694 features across 4340 samples within 1 assay
## Active assay: RNA (33694 features, 0 variable features)
pbmc8k.data <- Read10X(data.dir = "../data/pbmc8k/filtered_gene_bc_matrices/GRCh38/")
pbmc8k <- CreateSeuratObject(counts = pbmc8k.data, project = "PBMC8K")
pbmc8k
## An object of class Seurat
## 33694 features across 8381 samples within 1 assay
## Active assay: RNA (33694 features, 0 variable features)
合并两个Seurat对象merge()[2]合并两个对象的原始计数矩阵，并创建一个新的对象。 pbmc.combined <- merge(pbmc4k, y = pbmc8k, add.cell.ids = c("4K", "8K"), project = "PBMC12K")
pbmc.combined
## An object of class Seurat
## 33694 features across 12721 samples within 1 assay
## Active assay: RNA (33694 features, 0 variable features)
# notice the cell names now have an added identifier
head(colnames(pbmc.combined))
## [1] "4K_AAACCTGAGAAGGCCT-1" "4K_AAACCTGAGACAGACC-1" "4K_AAACCTGAGATAGTCA-1"
## [4] "4K_AAACCTGAGCGCCTCA-1" "4K_AAACCTGAGGCATGGT-1" "4K_AAACCTGCAAGGTTCT-1"
table(pbmc.combined$orig.ident)
##
## PBMC4K PBMC8K
## 4340 8381
合并两个以上的Seurat对象要合并两个以上的对象，只需将多个对象的向量传递到参数中即可：我们将使用 4K 和 8K PBMC 数据集以及我们以前计算的 2，700 PBMC的Seurat 对象来演示此情况。 library(SeuratData)
InstallData("pbmc3k")
pbmc3k <- LoadData("pbmc3k", type = "pbmc3k.final")
pbmc3k
## An object of class Seurat
## 13714 features across 2638 samples within 1 assay
## Active assay: RNA (13714 features, 2000 variable features)
## 2 dimensional reductions calculated: pca, umap
pbmc.big <- merge(pbmc3k, y = c(pbmc4k, pbmc8k), add.cell.ids = c("3K", "4K", "8K"), project = "PBMC15K")
pbmc.big
## An object of class Seurat
## 34230 features across 15359 samples within 1 assay
## Active assay: RNA (34230 features, 0 variable features)
head(colnames(pbmc.big))
## [1] "3K_AAACATACAACCAC" "3K_AAACATTGAGCTAC" "3K_AAACATTGATCAGC"
## [4] "3K_AAACCGTGCTTCCG" "3K_AAACCGTGTATGCG" "3K_AAACGCACTGGTAC"
tail(colnames(pbmc.big))
## [1] "8K_TTTGTCAGTTACCGAT-1" "8K_TTTGTCATCATGTCCC-1" "8K_TTTGTCATCCGATATG-1"
## [4] "8K_TTTGTCATCGTCTGAA-1" "8K_TTTGTCATCTCGAGTA-1" "8K_TTTGTCATCTGCTTGC-1"
unique(sapply(X = strsplit(colnames(pbmc.big), split = "_"), FUN = "[", 1))
## [1] "3K" "4K" "8K"
table(pbmc.big$orig.ident)
## pbmc3k PBMC4K PBMC8K
## 2638 4340 8381
基于标准化数据的合并默认情况下，将基于原始计数矩阵合并对象, 如果你想合并标准化的数据矩阵以及原始计数矩阵，则应这样做，添加merge.data = TRUE。 pbmc4k <- NormalizeData(pbmc4k)
pbmc8k <- NormalizeData(pbmc8k)
pbmc.normalized <- merge(pbmc4k, y = pbmc8k, add.cell.ids = c("4K", "8K"), project = "PBMC12K",
merge.data = TRUE)
GetAssayData(pbmc.combined)[1:10, 1:15]
## 10 x 15 sparse Matrix of class "dgCMatrix"
##
## RP11-34P13.3 . . . . . . . . . . . . . . .
## FAM138A . . . . . . . . . . . . . . .
## OR4F5 . . . . . . . . . . . . . . .
## RP11-34P13.7 . . . . . . . . . . . . . . .
## RP11-34P13.8 . . . . . . . . . . . . . . .
## RP11-34P13.14 . . . . . . . . . . . . . . .
## RP11-34P13.9 . . . . . . . . . . . . . . .
## FO538757.3 . . . . . . . . . . . . . . .
## FO538757.2 . . . . . . . . . 1 . . . . .
## AP006222.2 . . . . . . . . . . . 1 . . .
GetAssayData(pbmc.normalized)[1:10, 1:15]
## 10 x 15 sparse Matrix of class "dgCMatrix"
##
## RP11-34P13.3 . . . . . . . . . . . . . . .
## FAM138A . . . . . . . . . . . . . . .
## OR4F5 . . . . . . . . . . . . . . .
## RP11-34P13.7 . . . . . . . . . . . . . . .
## RP11-34P13.8 . . . . . . . . . . . . . . .
## RP11-34P13.14 . . . . . . . . . . . . . . .
## RP11-34P13.9 . . . . . . . . . . . . . . .
## FO538757.3 . . . . . . . . . . . . . . .
## FO538757.2 . . . . . . . . . 0.7721503 . . . . .
## AP006222.2 . . . . . . . . . . . 1.087928 . . .
参考资料[1]在这里: https://support./single-cell-gene-expression/datasets [2]merge(): https:///r/base/merge.html
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