forensim (version 1.1-4)

lik.loc: Likelihood per locus of the observed alleles in a DNA mixture conditional on the number of contributors to the mixture

Description

The lik.loc function computes the likelihood of the observed data in a forensic DNA mixture, for each of the loci involved, conditional on the number of contributors to the mixture.

Usage

lik.loc(x = 1, mix, freq, refpop = NULL, theta = NULL, loc=NULL)

Arguments

x

the number of contributors to the DNA mixture

mix

a simumix object which contains the mixture to be analyzed

freq

a tabfreq object from which to extract the allele frequencies

refpop

a factor giving the reference population in tabfreq from which to extract the allele frequencies

theta

a float from [0,1[ giving Wright's Fst coefficien. theta acounts for population subdivision while computing the likelihood of the data.

loc

the loci for which the likelihood shall be computed. Default (set to NULL) corresponds to all loci.

Value

• The function lik.loc returns a vector, of length the number of loci in loc, giving the likelihood of the data for each locus.

encoding

UTF-8

Details

lik.loc computes the likelihood per locus of the observed alleles. This function implements the general formula for the interpretation of DNA mixtures in case of subdivided populations (Curran et al, 1999), in the particular case where all contributors are unknown and belong to the same subpopulation. The Fst coefficient given in the theta argument allows accounting for population subdivision when all contributors belong to the same subpopulation.

References

Haned H, Pene L, Lobry JR, Dufour AB, Pontier D. Estimating the number of contributors to forensic DNA mixtures: Does maximum likelihood perform better than maximum allele count? J Forensic Sci, accepted 2010. Curran JM, Triggs CM, Buckleton J, Weir BS. Interpreting DNA Mixtures in Structured Populations. J Forensic Sci 1999;44(5): 987-995

See Also

lik for the overall loci likelihood, likestim and likestim.loc for the estimation of the number of contributors to a DNA mixture through likelihood maximization

Examples

data(strusa)
#simulation of 1000 genotypes from the Caucasian allele frequencies
gen<-simugeno(strusa,n=c(0,100,0))

#4-person mixture
mix4 <- simumix(gen,ncontri=c(0,4,0))
lik.loc(x=2,mix4, strusa, refpop="Cauc")
lik.loc(x=2,mix4, strusa, refpop="Afri")
#You may also want to try:
#likestim(mix4,strusa,refpop="Cauc")