1.有直接的標(biāo)準(zhǔn)10X數(shù)據(jù)（喜大普奔）
解壓縮后可以得到三個(gè)文件（barcodes.tsv/genes.tsv/matrix.mtx）线得，文件名修改到一模一樣
例如：GSE106273
下載后三個(gè)文件，解壓縮后文件名改為barcodes.tsv圈纺、genes.tsv材原、matrix.mtx（一個(gè)字也不差）
pbmc.data <- Read10X(data.dir = "C:/Users/fhche/Desktop/GSE106273")
pbmc <- CreateSeuratObject(counts = pbmc.data, project = "pbmc", min.cells = 3, min.features = 200)
head(pbmc@meta.data)
2.多個(gè)10X數(shù)據(jù)可以用merge函數(shù)合并
例如：GSE135927琅攘，只有一個(gè)raw data能下載
下載后整理成GSM4038043饮潦、GSM4038044兩個(gè)文件夾琐脏，分別含有barcodes.tsv南捂、genes.tsv、matrix.mtx三個(gè)文件
GSM4038043<- Read10X(data.dir = "C:/Users/fhche/Desktop/GSE135927/GSM4038043")
pbmc1 <- CreateSeuratObject(counts = GSM4038043,
min.cells = 3,
min.features = 200)
GSM4038044<- Read10X(data.dir = "C:/Users/fhche/Desktop/GSE135927/GSM4038044")
pbmc2 <- CreateSeuratObject(counts = GSM4038044,
min.cells = 3,
min.features = 200)
head(pbmc2@meta.data)
pbmc = merge(pbmc1, pbmc2,
add.cell.ids = c("GSM4038043", "GSM4038044"),
merge.data = TRUE)
as.data.frame(pbmc@assays$RNA@counts[1:10, 1:2])
head(pbmc@meta.data)
實(shí)際操作中旧找，目錄下需要存放gz壓縮文件溺健。兩個(gè)以上數(shù)據(jù)合并代碼如下：
##————————————————————多個(gè)樣本合并-----------------------------
dirs <- list.dirs(".\\GSE173193_RAW\\") #取得樣本文件所在目錄路徑，每個(gè)下面3個(gè)文件
dir_sample <- dirs[2:5]
dir_sample
dir_sample[3]
#讀入四個(gè)樣本
GSM5261695 <- Read10X(data.dir = dir_sample[1])
GSM5261696 <- Read10X(data.dir = dir_sample[2])
GSM5261699 <- Read10X(data.dir = dir_sample[3])
GSM5261700 <- Read10X(data.dir = dir_sample[4])
#生成四個(gè)Seurat對(duì)象，修改count鞭缭，其余默認(rèn)
pbmc1 <- CreateSeuratObject(counts = GSM5261695,min.cells = 3, min.features = 200)
pbmc2 <- CreateSeuratObject(counts = GSM5261696,min.cells = 3, min.features = 200)
pbmc3 <- CreateSeuratObject(counts = GSM5261699,min.cells = 3, min.features = 200)
pbmc4 <- CreateSeuratObject(counts = GSM5261700,min.cells = 3, min.features = 200)
head(pbmc2@meta.data)
#合并數(shù)據(jù)
pbmc = merge(x = pbmc1, y = c(pbmc2,pbmc3,pbmc4),
add.cell.ids = c("GSM5261695","GSM5261696","GSM5261699","GSM5261700"),
merge.data = TRUE)
as.data.frame(pbmc@assays$RNA@counts[1:10, 1:15])
head(pbmc@meta.data)
saveRDS(pbmc,"pe_and_control.rds")
