R中行的成對比較

Question

我有一個數據集，其中包含許多樣本中許多測試的結果。 樣本在數據集中復制。 我想比較每組重復樣本中重復樣本之間的測試結果。 我認為首先按SampleID拆分數據幀可能是最簡單的方法，這樣我可以獲得一個數據幀列表，每個SampleID都有一個數據幀。 一個樣本可能有2、3、4甚至5個重復，因此每個樣本組要比較的唯一行組合的數量是不同的。 我具有下面所闡述的邏輯。 我想在數據幀列表上運行一個函數並輸出匹配結果。 該函數將比較每組重復樣本中2行的唯一集合，並返回“ Match”，“ Mismatch”或NA值（如果缺少一個或兩個測試值）。 它還將返回兩個比較重復之間重疊的測試計數，匹配數和不匹配數。 最后，它將在其中包含一列樣本名稱及其行號粘貼在一起的列，這樣我就知道比較了兩個樣本（例如Sample1.1_Sample1.2）。 有人能指出我正確的方向嗎？

    #Input data structure
    data = as.data.frame(cbind(rbind("Sample1","Sample1","Sample2","Sample2","Sample2"),rbind("A","A","C","C","C"), rbind("A","T","C","C","C"), 
                 rbind("A",NA,"C","C","C"), rbind("A","A","C","C","C"), rbind("A","T","C","C",NA), rbind("A","A","C","C","C"),
                 rbind("A","A","C","C","C"), rbind("A",NA,"C","T","T"), rbind("A","A","C","C","C"), rbind("A","A","C","C","C")))

    colnames(data) = c("SampleID", "Test1","Test2","Test3","Test4","Test5","Test6","Test7","Test8","Test9","Test10")
    data 

    data.split = split(data, data$SampleID)


    ##Row comparison function
    #Input is a list of data frames. Each data frame contains results for replicates of the same sample.
    RowCompare = function(x){
      rowcount = nrow(x)
      ##ifelse(rowcount==2,
        ##compare row 1 to row 2
          ##paste sample names being compared together
          ##how many non-NA values overlap, keep value
          ##of those that overlap, how many match, keep value
          ##of those that overlap, how many do not match, keep value
      #ifelse(rowcount==3,
          ##compare row 1 to row 2
            ##paste sample names being compared together
            ##how many non-NA values overlap, keep value
            ##of those that overlap, how many match, keep value
            ##of those that overlap, how many do not match, keep value
          ##compare row 1 to row 3
            ##paste sample names being compared together
            ##how many non-NA values overlap, keep value
            ##of those that overlap, how many match, keep value
            ##of those that overlap, how many do not match, keep value
          ##compare row 2 to row 3
            ##paste sample names being compared together
            ##how many non-NA values overlap, keep value
            ##of those that overlap, how many match, keep value
            ##of those that overlap, how many do not match, keep value
      return(results)
    }

    #Output is a list of data frames - one for sample name
    out = lapply(names(data.split), function(x) RowCompare(data.split[[x]])) 

    #Row bind the list of data frames back together to one large data frame
    out.merge = do.call(rbind.data.frame, out) 
    head(out.merge)

    #Desired output
    out.merge = as.data.frame(cbind(rbind("Sample1.1_Sample1.2","Sample2.1_Sample2.2","Sample2.1_Sample2.3","Sample2.2_Sample2.3"),rbind("Match","Match","Match","Match"), 
                      rbind("Mismatch","Match","Match","Match"), rbind(NA,"Match","Match","Match"), rbind("Match","Match","Match","Match"), rbind("Mismatch","Match",NA,NA), 
                      rbind("Match","Match","Match","Match"), rbind("Match","Match","Match","Match"), rbind(NA,"Mismatch","Mismatch","Match"), rbind("Match","Match","Match","Match"), 
                      rbind("Match","Match","Match","Match"), rbind(8,10,9,9), rbind(6,9,8,8), rbind(2,1,1,1)))

    colnames(out.merge) = c("SampleID", "Test1","Test2","Test3","Test4","Test5","Test6","Test7","Test8","Test9","Test10", "Num_Overlap", "Num_Match","Num_Mismatch")
    out.merge

我確實在另一篇文章中看到的一件我認為可能有用的事情是，下面的行將創建一個具有唯一行組合的數據框，然后可以使用該行定義在各組復制樣本中要比較的行。 雖然不確定如何實現它。

    t(combn(nrow(data),2))

謝謝。

Answer 1

t(combn(nrow(data),2))使您處在正確的軌道上。 請參閱下面的說明。

testCols <- which(grepl("^Test\\d+",colnames(data)))

TestsCompare=function(x,y){
  ##how many non-NA values overlap
  overlaps <- sum(!is.na(x) & !is.na(y))
  ##of those that overlap, how many match
  matches <- sum(x==y, na.rm=T)
  ##of those that overlap, how many do not match
  non_matches <- overlaps - matches # complement of matches
  c(overlaps,matches,non_matches)
}

RowCompare= function(x){
  comp <- NULL
  pairs <- t(combn(nrow(x),2))
  for(i in 1:nrow(pairs)){
    row_a <- pairs[i,1]
    row_b <- pairs[i,2]
    a_tests <- x[row_a,testCols]
    b_tests <- x[row_b,testCols]
    comp <- rbind(comp, c(row_a, row_b, TestsCompare(a_tests, b_tests)))
  }
  colnames(comp) <- c("row_a","row_b","overlaps","matches","non_matches")
  return(comp)
}

out = lapply(data.split, RowCompare)

生產：

> out
$Sample1
     row_a row_b overlaps matches non_matches
[1,]     1     2        8       6           2

$Sample2
     row_a row_b overlaps matches non_matches
[1,]     1     2       10       9           1
[2,]     1     3        9       8           1
[3,]     2     3        9       9           0