Maximum likelihood estimation of the number of contributors to a forensic DNA mixture for a set of loci

Description

The likestim function gives multiloci estimation of the number of contributors to a forensic DNA mixture using likelihood maximization.

Usage

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likestim(mix, freq, refpop = NULL, theta = NULL, loc=NULL)

Arguments

mix

a simumix object

freq

a tabfreq object containing the allele frequencies to use for the calculation

refpop

the reference population from which to extract the allele frequencies used in the likelihood calculation. If tabfreq contains more than one population, refpop must be specified, otherwise, refpop is set to default (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 to be considered in the estimation. Default (set to NULL) corresponds to all loci.

Details

The number of contributors which maximizes the likelihood of the data observed in the mixture is searched in the discrete interval [1,6]. In most cases this interval is a plausible range for the number of contributors.

Value

A matrix of dimension 1 x 2, the first column, max, gives the maximum likelihood estimation of the number of contributors, the second column gives the corresponding likelihood value maxvalue.

Author(s)

Hinda Haned <h.haned@nfi.minvenj.nl>

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.

Egeland T, Dalen I, Mostad PF. Estimating the number of contributors to a DNA profile. Int J Legal Med 2003, 117: 271-275

Curran JM, Triggs CM, Buckleton J, Weir BS. Interpreting DNA Mixtures in Structured Populations. J Forensic Sci 1999, 44(5): 987-995

See Also

likestim.loc for maximum of likelihood estimations per locus

Examples

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data(strusa)
#simulation of 1000 genotypes from the Hispanic allele frequencies
gen<-simugeno(strusa,n=c(0,0,100))
#4-person mixture
mix4 <- simumix(gen,ncontri=c(0,0,4))
likestim(mix4,strusa,refpop="Hisp")

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