haplotypes (version 1.1.3.1)

pairPhiST-methods: Provides the pairwise PhiST between populations

Description

This function calculates pairwise PhiST between populations using the AMOVA framework.

Usage

# S4 method for Dna
pairPhiST(x,populations,indels="sic",nperm=99, negatives=FALSE, subset =NULL, 
showprogbar=TRUE)
# S4 method for dist
pairPhiST(x,populations,nperm=99, negatives=FALSE, subset=NULL,showprogbar=TRUE)
# S4 method for matrix
pairPhiST(x,populations,nperm=99,negatives=FALSE, subset=NULL,showprogbar=TRUE)

Value

a list with following components:

PhiST

a matrix giving the PhiST values between populations.

p

a matrix giving the p-values, or NULL if permutation test is not performed.

Arguments

x

an object of class Dna, "dist" or "matrix".

populations

a vector giving the populations, with one element per individual.

indels

the indel coding method to be used. This must be one of "sic", "5th" or "missing". Any unambiguous substring can be given. See distance for details.

nperm

the number of permutations. Set this to 0 to skip the permutation procedure.

negatives

boolean; if it is FALSE all negative PhiST values are replaced with zero.

subset

a vector of integers in the range [1, length(unique(populations))], only distances between selected population(s) and the rest of the populations are calculated. If it is NULL, all comparisons are done.

showprogbar

boolean; whether the progress bar is displayed or not displayed.

Methods

signature(x = "Dna")

signature(x = "dist")

signature(x = "matrix")

Author

Caner Aktas,

Details

The null distribution of pairwise PhiST under the hypothesis of no difference between the populations is obtained by permuting individuals between populations.

References

Excoffier, L., Smouse, P.E. and Quattro, J.M. (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics, 131, 479-491.

Examples

data("dna.obj")

### Method for signature 'Dna'.
x<-dna.obj
x<-dna.obj[c(1,20,21,26,27,28,30,3,4,7,13,14,15,16,23,24,25),,as.matrix=FALSE]
populations<-c("pop1","pop1","pop1","pop1","pop1","pop1","pop1","pop2",
"pop2","pop2","pop2","pop2","pop3","pop4","pop3","pop4","pop4")

##skip permutation testing
pst<-pairPhiST(x, populations, nperm=0)
pst

##allow negative PhiST values
pst<-pairPhiST(x, populations, nperm=0, negatives=TRUE)
pst

##Gaps as missing characters.
pst<-pairPhiST(x, populations, indels="m", nperm=0, negatives=TRUE)
pst

##using subset, second population against others
pst <-pairPhiST(x, populations, nperm=0,subset=c(2))
pst


if (FALSE) {
## 999 permutations.
pst<-pairPhiST(x, populations, nperm=999,showprogbar=TRUE)
pst

## random populations
x<-dna.obj
populations<-sample(1:4,nrow(x),replace=TRUE)
pst<-pairPhiST(x, populations, nperm=999,showprogbar=TRUE)
pst

## populations based on clusters
x<-dna.obj
d<-distance(x)
hc<-hclust(d,method="ward.D")
populations<-cutree(hc,4)
pst<-pairPhiST(x, populations, nperm=999,showprogbar=TRUE)
pst
}

### Method for signature 'dist'.
x<-dna.obj
x<-dna.obj[c(1,20,21,26,27,28,30,3,4,7,13,14,15,16,23,24,25),,as.matrix=FALSE]
populations<-c("pop1","pop1","pop1","pop1","pop1","pop1","pop1","pop2",
"pop2","pop2","pop2","pop2","pop3","pop4","pop3","pop4","pop4")
d<-distance(x)
pst<-pairPhiST(d, populations, nperm=0)
pst

### Method for signature 'matrix'.
x<-dna.obj
x<-dna.obj[c(1,20,21,26,27,28,30,3,4,7,13,14,15,16,23,24,25),,as.matrix=FALSE]
populations<-c("pop1","pop1","pop1","pop1","pop1","pop1","pop1","pop2",
"pop2","pop2","pop2","pop2","pop3","pop4","pop3","pop4","pop4")
d<-as.matrix(distance(x))
pst<-pairPhiST(d, populations, nperm=0)
pst