单细胞数据读取（二）之Read10X读不出来dgCMatrix报错

前面我们也遇到过10x的数据读取不进去，如果大家遇到下面的报错，可以通过修改10x的原始重新读取，详细可以见链接https://blog.csdn.net/weixin_43949246/article/details/121225791

当然，这次跟大家说的是另一种10x的数据，同样的，我们先说报错，如果出现dgTMatrix的报错，我们该怎么办呢？

这里给大家推荐一种解决方法，首先先定义个函数，修改读取的方式

read10x_ymc <- function(data.dir = NULL,gene.column = 2,unique.features = TRUE,strip.suffix = FALSE,prefix='',suffix="tsv"
) {full.data <- list()for (i in seq_along(along.with = data.dir)) {run <- data.dir[i]if (!dir.exists(paths = run)) {stop("Directory provided does not exist")}barcode.loc <- file.path(run, paste(prefix,'barcodes.',suffix,sep=''))gene.loc <- file.path(run, paste(prefix,'genes.',suffix,sep=''))features.loc <- file.path(run, paste(prefix,'features.',suffix,'.gz',sep=''))matrix.loc=file.path(run,paste(prefix,'matrix.mtx',sep=''))# Flag to indicate if this data is from CellRanger >= 3.0pre_ver_3 <- file.exists(gene.loc)if (!pre_ver_3) {addgz <- function(s) {return(paste0(s, ".gz"))}barcode.loc <- addgz(s = barcode.loc)matrix.loc <- addgz(s = matrix.loc)}if (!file.exists(barcode.loc)) {stop("Barcode file missing. Expecting ", basename(path = barcode.loc))}if (!pre_ver_3 && !file.exists(features.loc) ) {stop("Gene name or features file missing. Expecting ", basename(path = features.loc))}if (!file.exists(matrix.loc)) {print(matrix.loc)stop("Expression matrix file missing. Expecting ", basename(path = matrix.loc))}data <- readMM(file = matrix.loc) cell.names <- readLines(barcode.loc)if(!dim(data)[2]==length(cell.names)){data <- t(readMM(file = matrix.loc))}###这是与cellranger输出结果最大的不同if (all(grepl(pattern = "\\-1$", x = cell.names)) & strip.suffix) {cell.names <- as.vector(x = as.character(x = sapply(X = cell.names,FUN = ExtractField,field = 1,delim = "-")))}if (is.null(x = names(x = data.dir))) {if (i < 2) {colnames(x = data) <- cell.names} else {colnames(x = data) <- paste0(i, "_", cell.names)}} else {colnames(x = data) <- paste0(names(x = data.dir)[i], "_", cell.names)}feature.names <- read.delim(file = ifelse(test = pre_ver_3, yes = gene.loc, no = features.loc),header = FALSE,stringsAsFactors = FALSE)if (any(is.na(x = feature.names[, gene.column]))) {warning('Some features names are NA. Replacing NA names with ID from the opposite column requested',call. = FALSE,immediate. = TRUE)na.features <- which(x = is.na(x = feature.names[, gene.column]))replacement.column <- ifelse(test = gene.column == 2, yes = 1, no = 2)feature.names[na.features, gene.column] <- feature.names[na.features, replacement.column]}if (unique.features) {fcols = ncol(x = feature.names)if (fcols < gene.column) {stop(paste0("gene.column was set to ", gene.column," but feature.tsv.gz (or genes.tsv) only has ", fcols, " columns."," Try setting the gene.column argument to a value <= to ", fcols, "."))}rownames(x = data) <- make.unique(names = feature.names[, gene.column])}# In cell ranger 3.0, a third column specifying the type of data was added# and we will return each type of data as a separate matrixif (ncol(x = feature.names) > 2) {data_types <- factor(x = feature.names$V3)lvls <- levels(x = data_types)if (length(x = lvls) > 1 && length(x = full.data) == 0) {message("10X data contains more than one type and is being returned as a list containing matrices of each type.")}expr_name <- "Gene Expression"if (expr_name %in% lvls) { # Return Gene Expression firstlvls <- c(expr_name, lvls[-which(x = lvls == expr_name)])}data <- lapply(X = lvls,FUN = function(l) {return(data[data_types == l, , drop = FALSE])})names(x = data) <- lvls} else{data <- list(data)}full.data[[length(x = full.data) + 1]] <- data}list_of_data <- list()for (j in 1:length(x = full.data[[1]])) {list_of_data[[j]] <- do.call(cbind, lapply(X = full.data, FUN = `[[`, j))# Fix for Issue #913print('yaomengcheng')list_of_data[[j]] <- as(object = list_of_data[[j]], Class = "dgCMatrix")}names(x = list_of_data) <- names(x = full.data[[1]])# If multiple features, will return a list, otherwise# a matrix.if (length(x = list_of_data) == 1) {return(list_of_data[[1]])} else {return(list_of_data)}
}

这时候重新读取进去，这样问题就可以解决

my.data<-read10x_ymc(data.dir = 'L1/',gene.column =2, prefix='',suffix="tsv")
sce=CreateSeuratObject(counts = my.data, project = 'L1', #每个基因至少在3个细胞中表达，每一个细胞至少有250个基因表达min.cells = 3, min.features = 250)

其实这里出现的问题，最主要是出现在dgCMatrix包这个问题上，而R语言中dgCMatrix包是用来专门大型稀疏矩阵的，当然大家可选择性重新安装Matrix包，但是不一定能解决问题，最好的方式，可以通过上述的方法解决该问题。有问题的小伙伴也可以私信我哈！

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单细胞数据读取（二）之Read10X读不出来dgCMatrix报错

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