如何比较R中一个数据帧的行？

问题描述

我有一个包含很多行和至少13列的数据框。我需要将每一行与上一行进行比较，看看两列是否完全相同，其余各行是否不同。

如果两列中的两行相等，我想将这些行放在新的数据框中。

这是我的数据框。

前三行具有样本“ Sample”，但只有两行是相同的“ Gene”。第7行和第8行也具有相同的样本和基因。

我希望有一个新数据框，其中仅包含具有相同样本和相同基因的行。像这样：

我写了这段代码：

Vec_sample <- c()    
Vec_genes <- c()
Vec_variants <- c()
Vec_chr <- c()
Vec_coordinate <- c()
Vec_aa <- c()
Vec_Rs <- c()
`%notin%` <- Negate(`%in%`)


for (row in 1:nrow(dataframe))
{
  for (row_compare in 1:nrow(dataframe))
  {
    if ((dataframe$Gene[row] == dataframe$Gene[row_compare]) 
        & (row != row_compare))
    {
      if ((dataframe$Sample[row] %notin% Vec_sample) &
          (dataframe$Sample[row] == dataframe$Sample[row_compare]))
      {
        
        Vec_sample <- c(Vec_sample,dataframe$Sample[row])
        Vec_sample <- c(Vec_sample,dataframe$Sample[row_compare])
        Vec_genes <- c(Vec_genes,dataframe$Gene[row])
        Vec_genes <- c(Vec_genes,dataframe$Gene[row_compare])
        Vec_variants <- c(Vec_variants,dataframe$Variants[row])
        Vec_variants <- c(Vec_variants,dataframe$Variants[row_compare])
        Vec_chr <- c(Vec_chr,dataframe$Chr[row])
        Vec_chr <- c(Vec_chr,dataframe$Chr[row_compare])
        Vec_coordinate <- c(Vec_coordinate,dataframe$Coordinate[row])
        Vec_coordinate <- c(Vec_coordinate,dataframe$Coordinate[row_compare])
        Vec_aa <- c(Vec_aa,dataframe$aa[row])
        Vec_aa <- c(Vec_aa,dataframe$aa[row_compare])
        Vec_Rs <- c(Vec_Rs,dataframe$Rs[row])
        Vec_Rs <- c(Vec_Rs,dataframe$Rs[row_compare])
      }
    }
  }
}

最后，当循环结束时，我用结果创建一个数据框。

final_dataframe <- data.frame(Vec_sample,Vec_genes,Vec_variants,Vec_chr,Vec_coordinate,Vec_aa,Vec_Rs).

一切都是重复的，因为我需要一对相等的样本和基因（当然，其余信息也是如此）。 我写了两个for循环，因为我想将实际基因与另一个进行比较。

有问题吗？如果样本已经保存在向量“ Vec_sample”中，如果还有另一对样本相同，我的脚本将不会保存这对样本。 （例如，对于样本14-043，首先它将保存基因ALG9对，但是不会保存基因MNS1对。）

这是我的错误的新数据框。

我之所以说这样的例外，是因为当我运行两个循环时，该表将被检查一次以上，并且可以多次保存该基因并将其重复。

很抱歉，如果我的语法或编程方式效率低下，那我是从这个世界开始的，我并不是真正的专家。

我希望我对自己的解释很好。 预先非常感谢

我提供输入数据。

 structure(list(Sample = c("14-043","14-043","14-077","13-340","15-642","12-975"),Gene = c("ALG9","ALG10B","ALG9","SLC5A9","MNS1","GPI","HK3","HK3"),Variant = c("T>T/G","C>A/G","C>C/G","A>A/T","A>T/T","C>C/T","T>T/G","C>G/G","T>T/A","T>T/A"),Chr = c(4,4,13,2,20,8,8),Coordinate = c(23410158,3422351,23410451,2341043423,324652341,3246520,23410158,234541,23412341,23412341),aa = c("Gly44Thr","His8Pro","Ser44Thr","Thr4Pro","Ala45Ala","Ala45Leu","Gly44Thr","Phe3Ala","Val34His","Val34His"
),Rs = c("rs1715919","rs1734532413","rs1732413","rs173240","rs12305","rs10356","rs1715919","rs12342","rs9997","rs9997")),row.names = c(NA,-13L),class = "data.frame")

解决方法

如果我对您的理解正确，则可以使用dplyr:filter和lead使用lag来检查上一行和下一行

df <- structure(list(Sample = c("14-043","14-043","14-077","13-340","15-642","12-975"
),Gene = c("ALG9","ALG9","SLC5A9","MNS1","GPI","HK3"),Variant = c("T>T/G","C>C/G","A>A/T","A>T/T","C>C/T","T>T/G","C>G/G","T>T/A"),Chr = c(4,4,13,2,20,8),Coordinate = c(23410158,23410451,2341043423,324652341,3246520,23410158,234541,23412341),aa = c("Gly44Thr","Ser44Thr","Thr4Pro","Ala45Ala","Ala45Leu","Gly44Thr","Phe3Ala","Val34His"),Rs = c("rs1715919","rs1732413","rs173240","rs12305","rs10356","rs1715919","rs12342","rs9997")),row.names = c(NA,-11L),class = "data.frame")
library(tidyverse)
df %>% filter(Sample == lag(Sample) | Sample == lead(Sample),Gene == lag(Gene) | Gene == lead(Gene))
#>   Sample Gene Variant Chr Coordinate       aa        Rs
#> 1 14-043 ALG9   T>T/G   4   23410158 Gly44Thr rs1715919
#> 2 14-043 ALG9   C>C/G   4   23410451 Ser44Thr rs1732413
#> 3 14-043 MNS1   A>T/T   2  324652341 Ala45Ala   rs12305
#> 4 14-043 MNS1   C>C/T   2    3246520 Ala45Leu   rs10356
#> 5 14-077 ALG9   T>T/G   4   23410158 Gly44Thr rs1715919
#> 6 14-077 ALG9   C>C/G   4   23410451 Ser44Thr rs1732413
#> 7 15-642 MNS1   A>T/T   2  324652341 Ala45Ala   rs12305
#> 8 15-642 MNS1   C>C/T   2    3246520 Ala45Leu   rs10356

^{由reprex package（v0.3.0）于2020-08-11创建}