lik {forensim} | R Documentation |
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.
lik(x = 1, mix, freq, refpop = NULL, theta = NULL, loc=NULL)
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 |
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.
Hinda Haned <haned@biomserv.univ-lyon1.fr>
Haned H, Pontier D, Lobry JR, Pene L, Dufour AB.
Estimating the number of contributors to forensic DNA mixtures: Does maximum likelihood
perform better than maximum allele count? Submitted, 2009.
Curran JM, Triggs CM, Buckleton J, Weir BS. Interpreting DNA Mixtures in Structured Populations. J Forensic Sci 1999;44(5): 987-995
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
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"))