(This article was first published on

Recently I wrote a couple of small functions as a result of work done by myself and others in my lab group. The first is a function that determines what sites in a sequence alignment are ambiguous (i.e. not A, G, C or T). **The Praise of Insects**, and kindly contributed to R-bloggers)require(ape)This function utilises the bit-level coding scheme that Emmanuel Paradis developed for encoding sequences in R. The unambiguous bases A, G, C and T have the numeric values 136, 72, 40 and 24 respectively. This function figures out which sites don't have these values and returns a vector of TRUEs and FALSEs, TRUEs being ambiguous bases.

data(woodmouse)

is.ambig <- function(x){

x <- as.matrix(x)

bases <- c(136, 72, 40, 24)

ambig <- apply(x, 2, FUN=function(x) sum(as.numeric(!as.numeric(x) %in% bases)))

ambig > 0

}

is.ambig(woodmouse)

The second function is an implementation of Tajima's K, published as equation A3 in Tajima 1983

tajima.K <- function(x, prop = TRUE){This function calculates the mean number of sites that are different between any two sequences. As a default, it returns the result as a proportion of the length of the alignment. Setting prop = FALSE will return the result as the actual number of sites.

res <- mean(dist.dna(x, model="N"))

if(prop) res <- res/dim(x)[2]

res

}

tajima.K(woodmouse)

References:

Tajmia F. 1983. Evolutionary relationship of DNA sequences in finite populations.

*Genetics*105: 437-460.

To

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