Highlights
- •A large data set of NGM DNA mixtures of three, four, and five donors is analyzed.
- •The performance of the basic likelihood ratio model is evaluated on controlled NGM mixtures.
- •The effect of using a biased estimate for the drop-out probability is evaluated.
- •The effect of underestimating the true number of donors on the LRs is evaluated.
Abstract
The interpretation of mixed DNA profiles obtained from low template DNA samples has
proven to be a particularly difficult task in forensic casework. Newly developed likelihood
ratio (LR) models that account for PCR-related stochastic effects, such as allelic
drop-out, drop-in and stutters, have enabled the analysis of complex cases that would
otherwise have been reported as inconclusive. In such samples, there are uncertainties
about the number of contributors, and the correct sets of propositions to consider.
Using experimental samples, where the genotypes of the donors are known, we evaluated
the feasibility and the relevance of the interpretation of high order mixtures, of
three, four and five donors.
The relative risks of analyzing high order mixtures of three, four, and five donors,
were established by comparison of a ‘gold standard’ LR, to the LR that would be obtained
in casework. The ‘gold standard’ LR is the ideal LR: since the genotypes and number
of contributors are known, it follows that the parameters needed to compute the LR
can be determined per contributor. The ‘casework LR’ was calculated as used in standard
practice, where unknown donors are assumed; the parameters were estimated from the
available data. Both LRs were calculated using the basic standard model, also termed
the drop-out/drop-in model, implemented in the LRmix module of the R package Forensim.
We show how our results furthered the understanding of the relevance of analyzing
high order mixtures in a forensic context. Limitations are highlighted, and it is
illustrated how our study serves as a guide to implement likelihood ratio interpretation
of complex DNA profiles in forensic casework.
Keywords
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Article info
Publication history
Published online: November 24, 2014
Accepted:
November 16,
2014
Received in revised form:
November 14,
2014
Received:
August 4,
2014
Identification
Copyright
© 2014 Elsevier Ireland Ltd. Published by Elsevier Inc. All rights reserved.
