你如何将 for 循环的每次迭代的结果恢复到它自己的矩阵中？

编程问答 2022-05-22

问题描述

我有一个 for 循环，它获取列表中的每个示例文件，为该示例创建一个矩阵，然后将其存储到所有示例矩阵的一个大列表中。

这是我目前所做的：

# load in data ------------------------------------------------------------------

filePaths = getGEOSuppFiles("GSE124395") 
tarF <- list.files(path = "./GSE124395/",pattern = "*.tar",full.names = TRUE) 
untar(tarF,exdir = "./GSE124395/") 
gzipF <- list.files(path = "./GSE124395/",pattern = "*.gz",full.names = TRUE) 
ldply(.data = gzipF,.fun = gunzip) 

#running test loop -------------------------------------------------------------

testlist <- c("./GSE124395//GSM3531672_P301_3_CRYOMIXED11.coutt.csv","./GSE124395//GSM3531673_P301_4_CRYOMIXED12.coutt.csv","./GSE124395//GSM3531674_P301_5_HEP1_1_5.coutt.csv")

LoopList_test <- list()

for (i in 1:length(testlist)){
  
  matrix_test <- read.delim(file =testlist[i])
  matrix_test <- data.frame(matrix_test[,-1],row.names=matrix_test[,1]) 
  matrix_test <- as.matrix(matrix_test) #<- makes the excel file into a matrix 
  
  colname_test <- read.delim(file =testlist[i])
  colname_test <- read.table(file = './GSE124395//GSE124395_celseq_barcodes.192.txt',header = FALSE,row.names = 1) 
  colname_test <- data.frame(colname_test[,col=colname_test[,1]) 
  colname_test <- as.matrix(colname_test) 
  colnames(matrix_test) <- colname_test[,1] 
  
  LoopList_test[[i]]<-matrix_test
}

这是输出： part of output in the one big list

我希望循环将每次迭代的结果存储到它自己的矩阵中，所以如果有意义的话，我有多个矩阵而不是一个巨大的矩阵列表。我认为这涉及将这个巨大的列表拆分为子列表，或者将循环的结果存储到矩阵/数组/向量而不是列表中，或者以某种方式将每次迭代存储到循环内的自己的变量中。我不知道该怎么做。

感谢阅读！

更新：

所以这一切的重点是创建矩阵，然后将它们组合成一个矩阵。然后将这个矩阵转换为 Seurat 对象，然后我可以对其进行聚类。

所以这是我到目前为止所做的：基本上，我对数据集中的每个组进行了多次循环，添加了我需要的任何信息，然后获取列表，我认为我需要的函数实际上获取了一个列表，因此对我好。这是我目前决定的代码：

mylist<-list.files(path = "./GSE124395/",pattern = "\\.csv$",full.names = TRUE)

LoopList <- list()

for (i in 1:30){
  
  matrix_input <- read.delim(file =mylist[i])
  matrix_input <- data.frame(matrix_input[,row.names=matrix_input[,1]) 
  matrix_input <- as.matrix(matrix_input) #<- makes the excel file into a matrix 
  
  colname_input <- read.delim(file =mylist[i])
  colname_input <- read.table(file = './GSE124395//GSE124395_celseq_barcodes.192.txt',row.names = 1) 
  colname_input <- data.frame(colname_input[,col=colname_input[,1]) 
  colname_input <- as.matrix(colname_input) 
  colnames(matrix_input) <- colname_input[,1] 
  
  colnames(matrix_input) <- paste(colnames(matrix_input),"Colorectal_Metastasis",sep = "_")
  P301_pdat <- data.frame("samples" = colnames(matrix_input),"treatment" = "Colorectal_Metastasis") 
  
  sobj <- CreateSeuratObject(counts = matrix_input,min.cells = 0,min.features = 1,project = "Patient301_Colorectal_Metastasis")
  
  LoopList[[i]]<-sobj
  #LoopList <- assign(paste0("Patient301",i),sobj )
}



# P304 loop ------------------------------------------------------------------------- 


for (i in 31:56){
  
  matrix_input <- read.delim(file =mylist[i])
  matrix_input <- data.frame(matrix_input[,sep = "_")
  P304_pdat <- data.frame("samples" = colnames(matrix_input),project = "Patient304_Colorectal_Metastasis")
  
  LoopList[[i]]<-sobj
  
}

等等。然后，按照https://satijalab.org/seurat/articles/integration_large_datasets.html

sobj.list <- SplitObject(LoopList,split.by = "orig.ident")
joined <- lapply(X = LoopList,FUN = function(x) {
  x <- normalizeData(x,verbose = FALSE)
  x <- FindVariableFeatures(x,verbose = FALSE)
})


features <- SelectIntegrationFeatures(object.list = joined)
joined <- lapply(X = joined,FUN = function(x) {
  x <- ScaleData(x,features = features,verbose = FALSE)
  x <- RunPCA(x,verbose = FALSE)
})


anchors <- FindIntegrationAnchors(object.list = joined,reduction = "rpca",dims = 1:50)
joined.integrated <- IntegrateData(anchorset = anchors,dims = 1:50)

joined.integrated <- ScaleData(joined.integrated,verbose = FALSE)
joined.integrated <- RunPCA(joined.integrated,verbose = FALSE)
joined.integrated <- RunUMAP(joined.integrated,dims = 1:50)

DimPlot(joined.integrated,group.by = "orig.ident")
DimPlot(joined.integrated,reduction = "umap",split.by = "treatment")

我不知道这是否确实有效，但我想我会更新这个问题以反映我迄今为止学到的东西！我想我学到的教训是看看你是否能找到一个将列表作为输入的函数。

解决方法

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