DNA pairwise distances from R matrix

Question

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:

1. AGGTT
2. AGCTA
3. AGGTA

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

Answer 1

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