Hello,
I encounter two problems :
First, I need to modify some huge arrays (2000 individuals x 50 000
variables).
To format the data, I think I should benefit from optimized R-selection
and R-replacement inside a matrix and prohibite a naive use of loops.
Thank you in advance for providing information about the following problem :
file A :
2 000 individuals in rows
50 000 columns corresponding to 50 000 variables : each value belongs to
{0, 1, 2}
file B :
50 000 variables in rows
1st column : character (A,C,G,T) corresponding to code 0
2nd colomn : character corresponding to code 1
convention:
if A[,j]=0, one wants to replace 0 with character in B[j,1] twice
if A[,j]=1, one wants to replace 1 with character in B[j,1] and
character in B[j,2]
if A[,j]=2, one wants to replace 2 with character in B[j,2] and
character in B[j,2]
C <- matrix(0,2000,0) # initialization to void matrix
for(j in 1:2000){
c <- A[,j]
zeros <- which(c==0);
ones <- which(c==1);
twos <- which(c==2);
rm(c)
c1 <- matrix("Z",2000)
c2 <- matrix("Z",2000)
c1[zeros] <- B$V1[j]; c2[zeros] <-B$V1[j]
c1[ones] <- B$V1[j]; c2[ones] <-B$V2[j]
c1[twos] <- B$V2[j]; c2[twos] <-B$V2[j]
C <- cbind(C, cbind(c1,c2))
}
I do think some more elaborated solution might exist.
_______________________
However, testing this naive implementation restricting to 6 individuals
and variable number 6 (in B), I encounter the problem of character
strings coerced to numbers.
coding.txt
*allele0 allele1
A C
G T
A G
G C
G T
A T*
c <- data.frame(x=1:6,y=c(0,1,2,0,1,2))
A <- c$y
zeros <- which(A==0);
ones <- which(A==1);
twos <- which(A==2);
rm(A)
c1 <- matrix("Z",6)
c2 <- matrix("Z",6)
B <- read.table(file="coding.txt",h=T)
c1[zeros] <- B$allele0[6]; c2[zeros] <-B$allele0[6]
c1[ones] <- B$allele0[6]; c2[ones] <-B$allele1[6]
c1[twos] <- B$allele1[6]; c2[twos] <-B$allele1[6]
results obtained for c1 and c2 :
> c1
[,1]
[1,] "1"
[2,] "1"
[3,] "3"
[4,] "1"
[5,] "1"
[6,] "3"
> c2
[,1]
[1,] "1"
[2,] "3"
[3,] "3"
[4,] "1"
[5,] "3"
[6,] "3"
Thanks in advance for your help.
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