# rmp: Random match probability of profile(s) In DNAprofiles: DNA Profiling Evidence Analysis

## Description

Computes the random/conditional match probability.

## Usage

 1 2 rmp(x, freqs = get.freqs(x), markers = get.markers(x), theta = 0, cmp = FALSE, ret.per.marker = FALSE) 

## Arguments

 x Integer matrix with the profile(s) for which random match probability is computed. freqs A list specifying the allelic frequencies. Should contain a vector of allelic frequencies for each locus, named after that locus. markers Character vector stating the markers to use in the rmp computation. Defaults to all markers of the profile. theta Numeric value specifying the amount of background relatedness. cmp Logical conditional match probability. If TRUE, the Balding-Nichols formula is used to compute the conditional match probability in the same subpopulation. ret.per.marker Logical. If TRUE, return a matrix of random match probabilities, where the columns correspond to markers.

## Details

When θ=0, the simple product rule is used. Assuming Hardy-Weinberg and Linkage Equilibrium, the random match probability (rmp) for unordered is computed as the product of

2^H f_a f_b

over the loci, where f_a and f_b are respectively the population frequencies of allele a and b and H is the indicator function for heterozygosity (alleles a and b are not the same).

When θ>0 and cmp=FALSE, the product rule is used that incorporates a correction for inbreeding as measured by theta.

When θ>0 and cmp=TRUE, a product rule involving a subpopulation correction is used, as given by Balding & Nichols. The match probability for homozygotes is given by:

\frac{(2 θ+(1-θ)f_a)(3 θ+(1-θ)f_a)}{(1+θ)(1+2 θ)},

and for heterozygotes by:

\frac{2(θ+(1-θ)f_a)(θ+(1-θ)f_b)}{(1+θ)(1+2θ)}.

If x contains missing values (NAs) at a marker, then the returned match probability equals one for persons with both alleles missing. If a single allele is missing, then the match probability is equal to the frequency of the single allele that is seen, unless the conditional match probability is computed.

## Value

numeric matrix of random match probabilities. When ret.per.matrix is TRUE, the columns contain rmps per marker.

## Examples

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 ## compute the conditional match probability for two markers data(freqsNLngm) y <- sample.profiles(N=1,freqsNLngm) rmp(y,markers = c("FGA","TH01"),theta=0.03,cmp=TRUE,ret.per.marker = TRUE) rmp(y,markers = c("FGA","TH01"),ret.per.marker = TRUE) # compare to product rule estimate ## make a plot of density estimates of RMPs of profiles on the 10 SGMplus data(freqsNLsgmplus) #sample profiles x <- sample.profiles(N=1e3,freqsNLsgmplus) #compute RMPs x.rmp <- rmp(x) plot(density(log10(x.rmp)), xlab=expression(log(RMP)), main="Random match probabilities for SGMplus profiles") 

DNAprofiles documentation built on Jan. 15, 2017, 9:27 p.m.