Question

我有一个匹配列的矩阵（例如124G和124R）我想将匹配的列彼此分开。列不会根据匹配的ID进行排序，如下所示。任何人都可以提出这样做的功能吗？

                            124G      124R      126R      126G       26R       26G      243G…
hsa-let-7a-5p|hsa-let-7a-1 16659.1964 46129.599 53180.211 37259.453 61108.754 77946.898 87433.948
hsa-let-7a-5p|hsa-let-7a-2 16662.0615 46105.731 53185.511 37191.243 61115.984 77913.992 87379.138
hsa-let-7a-5p|hsa-let-7a-3 16639.4316 45986.194 53043.683 37157.778 60889.781 77855.132 87213.507
hsa-let-7b-5p|hsa-let-7b    8046.0040 16460.859 17660.545 20728.696 25369.899 26558.286 27932.843
hsa-let-7c-5p|hsa-let-7c     495.3461  1143.432  4671.550  1563.926  2078.405  4993.391  3479.066
hsa-let-7d-5p|hsa-let-7d    1682.8678  3879.721  4858.802  3062.387  4577.366  8218.718  7966.320

Answer 1

尝试

 sapply(split(colnames(m1),sub('[^0-9]+', '', colnames(m1))), function(x) {
              x1 <- m1[,sort(x)]
               x1[,1]/x1[,2]})


#                              124       126       243       26
#hsa-let-7a-5p|hsa-let-7a-1 0.3611390 0.7006263 1.0606547 1.275544
#hsa-let-7a-5p|hsa-let-7a-2 0.3613881 0.6992740 1.0362319 1.274855
#hsa-let-7a-5p|hsa-let-7a-3 0.3618354 0.7005128 1.0337772 1.278624
#hsa-let-7b-5p|hsa-let-7b   0.4887961 1.1737291 0.9823457 1.046842
#hsa-let-7c-5p|hsa-let-7c   0.4332099 0.3347767 1.0131058 2.402511
#hsa-let-7d-5p|hsa-let-7d   0.4337600 0.6302761 1.0817382 1.795513

或者

library(gtools)
indx <- mixedorder(colnames(m1))
m2 <- m1[,indx]
m2[,c(TRUE,FALSE)]/m2[,c(FALSE,TRUE)]
#                               26G      124G      126G      243G
#hsa-let-7a-5p|hsa-let-7a-1 1.275544 0.3611390 0.7006263 1.0606547
#hsa-let-7a-5p|hsa-let-7a-2 1.274855 0.3613881 0.6992740 1.0362319
#hsa-let-7a-5p|hsa-let-7a-3 1.278624 0.3618354 0.7005128 1.0337772
#hsa-let-7b-5p|hsa-let-7b   1.046842 0.4887961 1.1737291 0.9823457
#hsa-let-7c-5p|hsa-let-7c   2.402511 0.4332099 0.3347767 1.0131058
#hsa-let-7d-5p|hsa-let-7d   1.795513 0.4337600 0.6302761 1.0817382

或者以上可以写成

 m2[,seq(1, ncol(m2), 2)]/m2[, seq(2, ncol(m2), 2)]

数据

m1 <-  structure(c(16659.1964, 16662.0615, 16639.4316, 8046.004, 495.3461, 
1682.8678, 46129.599, 46105.731, 45986.194, 16460.859, 1143.432, 
3879.721, 53180.211, 53185.511, 53043.683, 17660.545, 4671.55, 
4858.802, 37259.453, 37191.243, 37157.778, 20728.696, 1563.926, 
3062.387, 61108.754, 61115.984, 60889.781, 25369.899, 2078.405, 
4577.366, 77946.898, 77913.992, 77855.132, 26558.286, 4993.391, 
8218.718, 87433.948, 87379.138, 87213.507, 27932.843, 3479.066, 
7966.32, 82433.94, 84323.92, 84363.93, 28434.84, 3434.06, 7364.37
), .Dim = c(6L, 8L), .Dimnames = list(c("hsa-let-7a-5p|hsa-let-7a-1", 
"hsa-let-7a-5p|hsa-let-7a-2", "hsa-let-7a-5p|hsa-let-7a-3",
 "hsa-let-7b-5p|hsa-let-7b", 
"hsa-let-7c-5p|hsa-let-7c", "hsa-let-7d-5p|hsa-let-7d"), c("124G", 
"124R", "126R", "126G", "26R", "26G", "243G", "243R")))

Answer 2

这是另一个以整洁的格式重塑数据的想法。它考虑了不匹配的列。

'6'

给出了：

"6"

注意：对于所有匹配的列，这会将library(dplyr) library(tidyr) as.data.frame(m2) %>% add_rownames("id") %>% gather(key, value, -id) %>% extract(key, into = c("number", "letter"), "([0-9]+)([A-Z]+)") %>% arrange(id, number, letter) %>% group_by(id, number) %>% summarise(value = sum(value / lead(value), na.rm = TRUE)) %>% spread(number, value)除以#Source: local data frame [6 x 5] # # id 124 126 243 26 #1 hsa-let-7a-5p|hsa-let-7a-1 0.3611390 0.7006263 0 1.275544 #2 hsa-let-7a-5p|hsa-let-7a-2 0.3613881 0.6992740 0 1.274855 #3 hsa-let-7a-5p|hsa-let-7a-3 0.3618354 0.7005128 0 1.278624 #4 hsa-let-7b-5p|hsa-let-7b 0.4887961 1.1737291 0 1.046842 #5 hsa-let-7c-5p|hsa-let-7c 0.4332099 0.3347767 0 2.402511 #6 hsa-let-7d-5p|hsa-let-7d 0.4337600 0.6302761 0 1.795513（字母顺序），并为不匹配的列返回G（您可以轻松如果需要，请用R替换它们。如果您想将0除以NA，请使用R代替G

数据

lag()

Answer 3

基础解决方案，这里没什么特别的。我们对列进行排序，因为它们都匹配 - 它们将自动排列为G，然后是R对应的列。然后我们用G，然后是R grep所有的colnames，然后我们将它们相互分开。

m1 <- m1[sort(colnames(m1)]
m1_g <- m1[,grep("G",colnames(m1))]
m1_r <- m1[,grep("R",colnames(m1))]
m1_new <- m1_g/m1_r
m1_new

                                124G      126G      26G      243G
hsa-let-7a-5p|hsa-let-7a-1 0.3611390 0.7006263 1.275544 1.0606547
hsa-let-7a-5p|hsa-let-7a-2 0.3613881 0.6992740 1.274855 1.0362319
hsa-let-7a-5p|hsa-let-7a-3 0.3618354 0.7005128 1.278624 1.0337772
hsa-let-7b-5p|hsa-let-7b   0.4887961 1.1737291 1.046842 0.9823457
hsa-let-7c-5p|hsa-let-7c   0.4332099 0.3347767 2.402511 1.0131058
hsa-let-7d-5p|hsa-let-7d   0.4337600 0.6302761 1.795513 1.0817382

将匹配列彼此分开

3 个答案:

数据