haplotypes (version 1.1.3.1)

pairnei-methods: Provides the average number of pairwise Nei's (D) differences between populations

Description

Function provides pairwise Nei's raw number of nucleotide differences between populations.

Usage

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

Value

a list with following components:

neidist

a matrix giving the average number of pairwise Nei's (D) differences between populations (below diagonal elements) and average number of pairwise differences within populations (diagonal elements).

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.

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 Nei's differences under the hypothesis of no difference between the populations is obtained by permuting individuals between populations.

References

Nei, M. and Li, W. H. (1979) Mathematical model for studying genetic variation in terms of restriction endonucleases. Proceedings of the National Academy of Sciences of the United States of America 76, 5269-5273.

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
pn<-pairnei(x, populations, nperm=0)
pn

#Between populations
as.dist(pn$neidist)

#Within populations
diag(pn$neidist)

##Gaps as missing characters.
pn <-pairnei(x, populations, indels="m", nperm=0)
pn

##using subset, third population against others
pn<-pairnei(x, populations, nperm=0,subset=c(3))
pn

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

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

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

### 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)
pn<-pairnei(d, populations,nperm=0)
pn

### 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))
pn<-pairnei(d, populations,nperm=0)
pn