2个表之间的高级数据匹配

时间:2013-07-01 15:05:19

标签: r compare bioinformatics genetics

我是R的新手,我需要建议处理这个问题:

我有2张桌子。表格的开头如下所示:

表1:

   SNP              Gene      Pval  Best_SNP    Best_Pval
rs2932538   ENSG00000007341 5.6007
rs10488631  ENSG00000064419 7.7461
rs12537284  ENSG00000064419 4.5544
rs3764650   ENSG00000064666 12.3401
rs10479002  ENSG00000072682 5.0141
rs6704644   ENSG00000072682 6.2306
rs2900211   ENSG00000072682 9.9022

表2:

Best_SNP          Gene      Best_Pval   
rs9028922   ENSG00000007341 10.7892
rs8233293   ENSG00000064666 89.342
rs3234432   ENSG00000072682 32.321
rs2892334   ENSG00000064419 43.235

表1包含每个基因的完整SNP列表。表2包含表1中出现的每种基因的最佳SNP和相应的最佳Pval。

我想要执行以下操作:匹配表1到表2中的每个Gene,然后从表2中复制Best_SNP和Best_Pval,并将它们粘贴到表1中针对该Gene的Best_SNP和Best_Pval列下。 棘手部分是在表1中,每个基因重复一个随机的,不同数量的行。例如,第二个基因ENSG00000064419重复2行,ENSG00000072682重复3行。因此,代码需要过滤基因的名称,并且只复制同一基因的Best_SNP和Best_Pval 一次

因此,对于基因ENSG00000072682,在3行中,只有看起来包含该基因的第一行需要填充Best_SNP和Best_Pval列。我不希望2个重复行的其余部分也有填写了Best_SNP和Best_Pval列。可以更容易地看到每个基因的起点和终点。

1 个答案:

答案 0 :(得分:0)

如果我理解正确,这就是解决方案:

x <- structure(list(SNP = c("rs2932538",  "rs10488631",  "rs12537284", "rs3764650",  
"rs10479002",  "rs6704644",  "rs2900211"), Gene = c("ENSG00000007341", "ENSG00000064419", 
"ENSG00000064419", "ENSG00000064666", "ENSG00000072682", "ENSG00000072682","ENSG00000072682"),
Pval= c(5.6007, 7.7461, 4.5544, 12.3401, 5.0141, 6.2306, 9.9022)), row.names= c(NA, 7L), class = "data.frame")

x
         SNP            Gene    Pval
1  rs2932538 ENSG00000007341  5.6007
2 rs10488631 ENSG00000064419  7.7461
3 rs12537284 ENSG00000064419  4.5544
4  rs3764650 ENSG00000064666 12.3401
5 rs10479002 ENSG00000072682  5.0141
6  rs6704644 ENSG00000072682  6.2306
7  rs2900211 ENSG00000072682  9.9022

x1 <- x[!(duplicated(x$Gene) | duplicated(x$Gene, fromLast = FALSE)), ]

x1
         SNP            Gene    Pval
1  rs2932538 ENSG00000007341  5.6007
2 rs10488631 ENSG00000064419  7.7461
4  rs3764650 ENSG00000064666 12.3401
5 rs10479002 ENSG00000072682  5.0141

y <- structure(list(Best_SNP = c("rs9028922", "rs8233293", "rs3234432", "rs2892334"), Gene =  c("ENSG00000007341", "ENSG00000064666",  
"ENSG00000072682",  "ENSG00000064419" ),
Best_Pval= c(10.7892, 89.342, 32.321, 43.235)), row.names= c(NA, 4L), class = "data.frame")

y
   Best_SNP            Gene Best_Pval
1 rs9028922 ENSG00000007341   10.7892
2 rs8233293 ENSG00000064666   89.3420
3 rs3234432 ENSG00000072682   32.3210
4 rs2892334 ENSG00000064419   43.2350


merge(x1, y, by="Gene", all= FALSE)

             Gene        SNP    Pval  Best_SNP Best_Pval
1 ENSG00000007341  rs2932538  5.6007 rs9028922   10.7892
2 ENSG00000064419 rs10488631  7.7461 rs2892334   43.2350
3 ENSG00000064666  rs3764650 12.3401 rs8233293   89.3420
4 ENSG00000072682 rs10479002  5.0141 rs3234432   32.3210