Likelihood of the observed alleles at different loci in a DNA mixture conditional on the number of contributors to the mixture

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Description

The lik function computes the likelihood of the observed alleles in a forensic DNA mixture, for a set of loci, conditional on the number of contributors to the mixture. The overall likelihood is computed as the product of loci likelihoods.

Usage

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

Arguments

x

the number of contributors to the DNA mixture, default is 1

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. This argument is used only if freq contains allele frequencies for multiple populations, otherwise it is by default set to NULL

theta

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

loc

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

Details

lik computes the likelihood of the alleles observed at all loci conditional on the number of contributors. This function implements the general formula for the interpretation of DNA mixtures in case of population subdivision (Curran et al, 1999), in the particular case where all contributors are unknown and belong to the same subpopulation.
The likelihood for multiple loci is computed as the product of loci likelihoods.

Author(s)

Hinda Haned <contact@hindahaned.info>

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.loc for the likelihood per locus, likestim and likestim.loc for the estimation of the number of contributors to a DNA mixture through likelihood maximization

Examples

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data(strusa)
#simulation of 1000 genotypes from the African American allele frequencies
gen<-simugeno(strusa,n=c(1000,0,0))
#3-person mixture
mix3<-simumix(gen,ncontri=c(3,0,0))
sapply(1:3, function(i) lik(x=i,mix3, strusa, refpop="Afri"))

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