Highlights
- •A series of novel formulae are provided to calculate the pedigree likelihood.
- •The formulae are deduced based on inheritance vectors and Lander-Green algorithm.
- •The formulae are deduced based on founder symmetry and founder couple symmetry.
- •The pedigree likelihood for multiple linked loci can be obtained by using the formulae.
- •A series of cases were designed based on three linked STR markers, on chromosome 6.
Abstract
Pedigree likelihood ratios are widely used in forensic genetics. Linkage of genetic
markers affects the pedigree likelihood ratio. In this study, a series of novel formulae
was established based on simplification due to founder and founder couple symmetry
of the Lander-Green algorithm for dealing with linkage. These new formulae are based
on the inheritance vectors and differ from existing formulae that are based on the
number of alleles shared identical-by-descent. In contrast to previous formulae, the
formulae of this study expand the calculation to more general relationships, which
enables specifying the number of typed individuals in pedigrees, and the new formulae
are no longer limited to calculation of pairs of linked markers. Alternatively, pedigree
likelihood values incorporating multiple linked markers could be obtained by iterating
the vector transition probability between pairs of linkage markers and the probability
of genotypes of typed individuals given inheritance vectors; the vector transition
probability formulae are provided in a table form. To demonstrate utilization of the
proposed formulae system, a series of cases were designed based on the relationships
to validate GeneVisa software (www.genevisa.net) with frequency data of three linked markers, SE33-D6S1043-D6S474, on chromosome
6. The calculation results were verified with the FamLink software. The results demonstrated
that the proposed formulae can correctly obtain the pedigree likelihood ratio, demonstrating
the application potential of these formulae to verify effectiveness of DNA testing
software.
Keywords
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Article info
Publication history
Published online: October 17, 2022
Accepted:
September 26,
2022
Received in revised form:
September 24,
2022
Received:
February 11,
2022
Identification
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