How to split each of the columns in a data frame to two column?

Question

I have a data frame which is like this(4 rows and 5 column):

Marker ind1 ind2 ind3 ind4
mark1             CT             TT             CT             TT
mark2             AG             AA             AG             AA
mark3             AC             AA             AC             AA
mark4             CT             TT             CT             TT

what I want to do is to split each of the columns (except first coloumn) to two column. so the output should be like this (4 rows and 9 column):

Marker ind1 ind1 ind2 ind2 ind3 ind3 ind4 ind4
mark1             C T             T T             C T             T T
mark2             A G             A A             A G             A A
mark3             A C             A A             A C             A A
mark4             C T             T T             C T             T T

I know how to split one column

do.call(rbind,strsplit(test$JRP4RA6119.039, ""))

which gives this:

      [,1] [,2]
 [1,] "C"  "T" 
 [2,] "A"  "G" 
 [3,] "A"  "C" 
 [4,] "C"  "T" 

what I would like is to be able to loop this and make it for all columns in one dataframe.

Thanks in advance.

Answer 1

I've got the feeling that it is a bit far-fetched but:

test_split <- data.frame(Marker=test$Marker, 
                         do.call("cbind", lapply(apply(test[, -1], 2, strsplit, ""), 
                                                 function(x) do.call("rbind", x))), 
                         stringsAsFactors=F)
colnames(test_split)[-1] <- paste(rep(colnames(test)[-1], e=2), 1:2, sep="_")

test_split
#      Marker JRP4RA6119.039_1 JRP4RA6119.039_2 JRP4RA6124.029_1 JRP4RA6124.029_2 JRP4RA6133.051_1 JRP4RA6133.051_2 JRP4RA6125.009_1 JRP4RA6125.009_2
#1 s7e4419xxx                C                T                T                T                C                T                T                T
#2 s7e7001s01                A                G                A                A                A                G                A                A
#3 s7e3049xxx                A                C                A                A                A                C                A                A
#4 s7e4727xxx                C                T                T                T                C                T                T                T