A comparative study of qualitative and quantitative models used to interpret complex STR DNA profiles

Abstract

The investigation of the performance of models to interpret complex DNA profiles is best undertaken using real DNA profiles. Here we used a data set to reflect the variety typically encountered in real casework. The "crime-stains" were constructed from known individuals and comprised a total of 59 diverse samples: pristine DNA/DNA extracted from blood, 2-3 person mixtures, degradation/no-degradation, differences in allele sharing, dropout/no dropout, etc. Two siblings were also included in the test-set in order to challenge the systems. Two kinds of analyses were performed, namely tests on whether a person of interest is a contributor based on weight-of-evidence (likelihood ratio) calculations, and deconvolution test to estimate the profile of unknown constituent parts. The weight-of-evidence analyses compared LRmix Studio with EuroForMix including exploration of the effect of applying an ad hoc stutter-filter. For the deconvolution analysis we compared EuroForMix with LoCIM-tool. When we classified persons of interests into being true contributors or non-contributors, we found that EuroForMix, overall, returned a higher true positive rate for the same false positive levels compared to LRmix. In particular, in cases with an unknown major component, EuroForMix was more discriminating for mixtures where the person of interest was a minor contributor. Comparing deconvolution of major contributors we found that EuroForMix overall performed better than LoCIM-tool.

Deconvolution of blood-blood mixtures using DEPArrayTM separated single cell STR profiling

“…As a further approach, the sex-specific labelling of cells combined with laser microdissection is used for the isolation of cells from a male and a female contributor [1,2]. Moreover, some probabilistic models included in statistical software programs were used for mixture deconvolution [5,11].…”

DNA mixtures interpretation – A proof-of-concept multi-software comparison highlighting different probabilistic methods’ performances on challenging samples

“…Even though this outcome was expected, further analyses might indicate which DNA amplification kits would turned out to be the most useful in cases of Low-Template DNA. Obviously, theThese evaluations relative to these DNA mixtures just represent a proof-of-conceptsome evidence that fullycontinuous model seems to be the most suitable bio-statistical methodology to be performed by analysts when Low-Template DNA mixtures or major/minor mixtures, where the minor contributor is evidential[50], have to be interpreted from a probabilistic point-of-view. Furthermore, the fullycontinuous model is more effective to determine the contributors' ratios.…”

Using EuroForMix to analyse complex SNP mixtures, up to six contributors

“…The likelihood ratios were calculated based on either a qualitative model (LRmix) or a quantitative model (Euroformix) using the Rpackages forensim [5] and euroformix [4]. The maximum likelihood (ML) approach as described in [6] were performed for the two models. The component SNP allele frequencies used are those compiled by the 1000 Genomes Project Consortium [7] for five European populations, with a θ-correction, Fst = 0.01.…”