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答读者问（八）为什么Read10X也会报错?
往期回顾
问题
最近有读者表示看了我的这一讲（手把手教你做单细胞测序数据分析（二）——各类输入文件读取）以后并不能读入自己下载的10X数据（GSE176078），读取时遇到了以下的错误。显然我是不能背这个锅的，让我们来找找问题在哪，并给出解决办法。
怎么解决问题
首先，我反复强调过，遇到报错不要慌，要先看看R反馈给你什么错误，这里Error明显发生在feature文件中。在数据读取那一讲中，我们是把barcodes.tsv、feature.tsv（或gene.tsv）、matrix.tsv都用excel打开给大家看过数据结构，正常的是下图左的形式，而本次用到的数据打开是下图右的形式，这可能是版本因素造成的。所以问题很简单，正常的feature文件拥有两列，一列是ensemble ID，一列是基因的symbol（这个我们当时也给大家展示过，从2分钟开始看：https://www.bilibili.com/video/BV1S44y1b76Z?p=3），而这里少了一列。最简单的方法就是复制粘贴，把这个一列的文件变两列
改成两列后重新运行，就可以成功读入了。
那如果想以修改代码的方式解决这个问题呢？其实也很简单，我们来看一下Read10X()函数的源码，虽然这个代码很长，大概一百多行，但是在参数栏中已经指出了gene.column为2，那么我们只需要将这个参数修改为1，即可读入GSE176078中的数据。不过注意，修改过的函数可能无法调用Seurat的依赖包，所以需要额外加载，按我下面的代码操作即可。
更改后的代码：
library(Seurat)library(Matrix)myread10x <- function (data.dir, gene.column = 1, cell.column = 1, unique.features = TRUE, strip.suffix = FALSE) { 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, "barcodes.tsv") gene.loc <- file.path(run, "genes.tsv") features.loc <- file.path(run, "features.tsv.gz") matrix.loc <- file.path(run, "matrix.mtx") pre_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)) { stop("Expression matrix file missing. Expecting ", basename(path = matrix.loc)) } data <- readMM(file = matrix.loc) cell.barcodes <- read.table(file = barcode.loc, header = FALSE, sep = "\t", row.names = NULL) if (ncol(x = cell.barcodes) > 1) { cell.names <- cell.barcodes[, cell.column] } else { cell.names <- readLines(con = barcode.loc) } if (all(grepl(pattern = "\\-1$", x = cell.names)) & strip.suffix) { cell.names <- as.vector(x = as.character(x = sapply(X = cell.names, FUN = ExtractField, field = 1, delim = "-"))) } if (is.null(x = names(x = data.dir))) { if (length(x = data.dir) < 2) { colnames(x = data) <- cell.names } else { colnames(x = data) <- paste0(i, "_", cell.names) } } else { colnames(x = data) <- paste0(names(x = data.dir)[i], "_", cell.names) } feature.names <- read.delim(file = ifelse(test = pre_ver_3, yes = gene.loc, no = features.loc), header = FALSE, stringsAsFactors = FALSE) if (any(is.na(x = feature.names[, gene.column]))) { warning("Some features names are NA. Replacing NA names with ID from the opposite column requested", call. = FALSE, immediate. = TRUE) na.features <- which(x = is.na(x = feature.names[, gene.column])) replacement.column <- ifelse(test = gene.column == 2, yes = 1, no = 2) feature.names[na.features, gene.column] <- feature.names[na.features, replacement.column] } if (unique.features) { fcols = ncol(x = feature.names) if (fcols < gene.column) { stop(paste0("gene.column was set to ", gene.column, " but feature.tsv.gz (or genes.tsv) only has ", fcols, " columns.", " Try setting the gene.column argument to a value <= to ", fcols, ".")) } rownames(x = data) <- make.unique(names = feature.names[, gene.column]) } if (ncol(x = feature.names) > 2) { data_types <- factor(x = feature.names$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) { lvls <- 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)) list_of_data[[j]] <- as(object = list_of_data[[j]], Class = "dgCMatrix") } names(x = list_of_data) <- names(x = full.data[[1]]) if (length(x = list_of_data) == 1) { return(list_of_data[[1]]) } else { return(list_of_data) }}
myread10xcount <- myread10x('GSE176078_Wu_etal_2021_BRCA_scRNASeq/onecols/')所以呢，如果大家按照我的教程走，出了错，那肯定是你没有完全跟着我的教程走。遇到报错，核心问题无法是“代码敲错”、“数据格式不对”、“版本不一致”。我的教程还是比较详细的，几乎涵盖所有常见问题，自己细心的跟着我的视频核对一下其实就能发现问题所在。当然，实在找不到问题在哪，也别自己硬扛着浪费时间，欢迎带着你的问题来找我。
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