R. Recode columns based on values of other 2 columns that have different levels

Question

I have a data frame with 10000 rows and 1000 columns that looks like this:

ID    a0    a1    V1    V2    V3
rs1   G     A     0     0     1
rs2   C     T     1     0     0
rs3   T     C     0     1     1    

a0 and a1 can be A, T, C or G, and indicate whether the other columns are 0 or 1. For instance, in the second row, a0 = G and a1 = A, so V1 = 0 (G), V2 = 0 (G) and V3 = 1 (A). I expect an output data frame like this:

ID    a0    a1    V1    V2    V3
rs1   G     A     G     G     A
rs2   C     T     T     C     C
rs3   T     C     T     C     C

Many thanks

Answer 1

We can use lapply and ifelse to perform the replacement.

dat[, -(1:3)] <- lapply(dat[, -(1:3)], function(x){
  x <- ifelse(x == 0, dat[, 2], dat[, 3])
  return(x)
})

dat
#    ID a0 a1 V1 V2 V3
# 1 rs1  G  A  G  G  A
# 2 rs2  C  T  T  C  C
# 3 rs3  T  C  T  C  C

DATA

dat <- read.table(text = "ID    a0    a1    V1    V2    V3
rs1   G     A     0     0     1
rs2   C     T     1     0     0
rs3   T     C     0     1     1",
                  header = TRUE, stringsAsFactors = FALSE)