DNAtools (version 0.1-8)

dbExpect: Expected value of cell counts in DNA database comparison

Description

Computes the expected number of cell counts when comparing DNA profiles in a DNA database. For every pair of DNA profiles in a database the number of matching and partial matching loci is recorded. A match is declared if the two DNA profiles coincide for both alleles in a locus and a partial-match is recorded if only one allele is shared between the profiles. With a total of L loci the number of matching loci is 0,...,L and partial number of matches is 0,...,L-m, where m is the number of matching loci.

Usage

dbExpect(probs,theta=0,k=c(0,0,1),n=1,round=FALSE,na=TRUE,
         vector=FALSE,collapse=FALSE,wildcard=FALSE)

Arguments

probs

List of vectors with allele probabilities for each locus

theta

The coancestery coefficient

k

The vector of identical-by-descent probabilities, k=(k2,k1,k0), where for full-siblings k=c(1,2,1)/4. The default is k=c(0,0,1) refering to unrelated individuals.

n

Number of DNA profiles in the database

round

Whether or not the results should be rounded or not

na

Whether or not the off-elements should be returned as 0 or NA

vector

Whether or not the result should be returned as a matrix or vector. Note if 'collapse' is TRUE vector is ignored.

collapse

Logical (default FALSE). If TRUE the (m,p)-matrix will be collapased into a (2*m+p)-vector containing the total number of matching alleles.

wildcard

Should wildcards be used?

Value

• Returns a matrix (or vector, see above) of expected cell counts.

Details

Computes the expected cell counts using a recursion formula. See Tvedebrink et al (2011) for details.

References

T Tvedebrink, PS Eriksen, J Curran, HS Mogensen, N Morling. 'Analysis of matches and partial-matches in Danish DNA reference profile database'. Forensic Science International: Genetics, 2011.

Examples

## Simulate some allele frequencies:
  freqs <-  replicate(10, { g = rgamma(n=10,scale=4,shape=3); g/sum(g)},
              simplify=FALSE)
  ## Compute the expected number for a DB with 10000 profiles:
  dbExpect(freqs,theta=0,n=10000)