如何比较两个数据帧/表并在R中提取数据？

Question

为了提取下面两个数据帧之间的不匹配,我已经设法创建了一个新的数据帧,其中不匹配被替换.
我现在需要的是一系列不匹配:

dfA <- structure(list(animal1 = c("AA", "TT", "AG", "CA"), animal2 = c("AA", "TB", "AG", "CA"), animal3 = c("AA", "TT", "AG", "CA")), .Names = c("animal1", "animal2", "animal3"), row.names = c("snp1", "snp2", "snp3", "snp4"), class = "data.frame")
# > dfA
#      animal1 animal2 animal3
# snp1      AA      AA      AA
# snp2      TT      TB      TT
# snp3      AG      AG      AG
# snp4      CA      CA      CA
dfB <- structure(list(animal1 = c("AA", "TT", "AG", "CA"), animal2 = c("AA", "TB", "AG", "DF"), animal3 = c("AA", "TB", "AG", "DF")), .Names = c("animal1", "animal2", "animal3"), row.names = c("snp1", "snp2", "snp3", "snp4"), class = "data.frame")
#> dfB
#     animal1 animal2 animal3
#snp1      AA      AA      AA
#snp2      TT      TB      TB
#snp3      AG      AG      AG
#snp4      CA      DF      DF

为澄清不匹配,这里将它们标记为00:

#      animal1 animal2 animal3
# snp1      AA      AA      AA
# snp2      TT      TB      00
# snp3      AG      AG      AG
# snp4      CA      00      00

我需要以下输出:

structure(list(snpname = structure(c(1L, 2L, 2L), .Label = c("snp2", "snp4"), class = "factor"), animalname = structure(c(2L, 1L, 2L), .Label = c("animal2", "animal3"), class = "factor"), alleledfA = structure(c(2L, 1L, 1L), .Label = c("CA", "TT"), class = "factor"), alleledfB = structure(c(2L, 1L, 1L), .Label = c("DF", "TB"), class = "factor")), .Names = c("snpname", "animalname", "alleledfA", "alleledfB"), class = "data.frame", row.names = c(NA, -3L))
#  snpname animalname alleledfA alleledfB
#1    snp2    animal3        TT        TB
#2    snp4    animal2        CA        DF
#3    snp4    animal3        CA        DF

到目前为止,我一直在尝试从我的lapply函数中提取其他数据,我用它来将错误替换为零,但没有成功.我也尝试编写ifelse函数但没有成功.希望你们能在这里帮助我!

最终,这将针对尺寸为100K×1000的数据集运行,因此效率非常高

Answer 1

这个问题有data.table标签,所以这是我尝试使用这个包.第一步是将行名称转换为列,data.table不像那些那样,然后在rbind每个数据集设置一个id 之后转换为长格式,找到有多个唯一值的位置并转换回宽格式

library(data.table)  
setDT(dfA, keep.rownames = TRUE) 
setDT(dfB, keep.rownames = TRUE)   

dcast(melt(rbind(dfA, 
                 dfB, 
                 idcol = TRUE), 
           id = 1:2
           )[, 
             if(uniqueN(value) > 1L) .SD, 
             by = .(rn, variable)], 
      rn + variable ~ .id)

#      rn variable  1  2
# 1: snp2  animal3 TT TB
# 2: snp4  animal2 CA DF
# 3: snp4  animal3 CA DF