Highlights
- •Correctly assuming relatedness increases likelihood ratios for true donors.
- •Ignoring relatedness is conservative in most cases.
- •Potential relatedness may be modelled probabilistically.
Abstract
When evaluating support for the contribution of a person of interest (POI) to a mixed
DNA sample, it is generally assumed that the mixture contributors are unrelated to
the POI and to each other. In practice, there may be situations where this assumption
is violated, for instance if two mixture contributors are siblings. The effect on
the likelihood ratio of (in)correctly assuming relatedness between mixture contributors
has previously been investigated using simulation studies based on simplified models
ignoring peak heights. We revisit this problem using a simulation study that applies
peak height models both in the simulation and mixture interpretation part of the study.
Specifically, we sample sets of mixtures comprising both related and unrelated contributors
and evaluate support for the contribution of the mixture donors as well as unrelated
persons with and without incorporating an assumption of relatedness. The results show,
consistent with earlier studies, that including a correct assumption of relatedness
increases the capacity of the probabilistic genotyping system to distinguish between
mixture donors and unrelated persons. Any effect of the relatedness is found to depend
strongly on the mixture ratio. We further show that the results do not change materially
when a sub-population correction is applied. Finally, we suggest and discuss a likelihood
ratio approach that considers relatedness between mixture contributors using a prior
probability.
Keywords
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Article info
Publication history
Published online: October 26, 2022
Accepted:
October 14,
2022
Received in revised form:
September 21,
2022
Received:
July 10,
2022
Identification
Copyright
© 2022 Elsevier B.V. All rights reserved.
