When working with DNA, we often need the triangular p-distance matrix, which contains the proportion of non-identical sites between pairs of sequences. Thus:
Yields:
1 2
2 0.4
3 0.2 0.2
The p-distance calculation is available in certain R packages, but suppose I need to use numerical code (-1,0,1,2), rather than letters (C,T,A,G). How do I generate the triangular p-distance matrix from "my.matrix"?
# Define DNA matrix dimensions
bp = 5 # DNA matrix length
n = 3 # DNA matrix height
# Build Binary Matrices
purine <- matrix(sample(0:1,(bp*n),replace=TRUE,prob=c(0.5,0.5)),n,bp)
ketone <- matrix(sample(0:1,(bp*n),replace=TRUE,prob=c(0.5,0.5)),n,bp)
strong <- 1-(abs(purine-ketone))
my.matrix <- (purine*strong-ketone)+(purine*ketone-strong)+purine+ketone
my.matrix
I'm not sure what you are doing with my.matrix, but this should work with either characters or numbers
x<-c("AGGTT", "AGCTA", "AGGTA")
y<-do.call("rbind", strsplit(x, ""))
y
[,1] [,2] [,3] [,4] [,5]
[1,] "A" "G" "G" "T" "T"
[2,] "A" "G" "C" "T" "A"
[3,] "A" "G" "G" "T" "A"
z <- apply(y, 1, function(x) colMeans(x != t(y)) )
z
[,1] [,2] [,3]
[1,] 0.0 0.4 0.2
[2,] 0.4 0.0 0.2
[3,] 0.2 0.2 0.0
And you can probably use lower or upper.tri to get a triangle if needed. Also, if the apply function looks confusing, it's just applying this function to all three rows...
y[1,] == t(y)
[,1] [,2] [,3]
[1,] TRUE TRUE TRUE
[2,] TRUE TRUE TRUE
[3,] TRUE FALSE TRUE
[4,] TRUE TRUE TRUE
[5,] TRUE FALSE FALSE
...and this returns the first row in the distance matrix
colMeans(y[1,] != t(y))
[1] 0.0 0.4 0.2