Journal of Forensic Sciences · 2021 · 16 citations · 26 references
Life SciencesGeneticsMolecular GeneticsGenomic Data AnalysisGenomicsMedical GeneticsDna SequencingMolecular MarkersExpected CountsMarkov Chain Monte Carlo InferencePeak Concentration VariabilityPolymerase Chain Reaction Amplification EfficiencyShort Tandem Repeat DetectionShort Tandem RepeatsVariable Number Tandem Repeat AnalysisVariances
We describe an adaption of Bright et al.'s work modeling peak height variability in CE-DNA profiles to the modeling of allelic aSTR (autosomal short tandem repeats) read counts from NGS-DNA profiles, specifically for profiles generated from the ForenSeq™ DNA Signature Prep Kit, DNA Primer Mix B. Bright et al.'s model consists of three key components within the estimation of total allelic product-template, locus-specific amplification efficiencies, and degradation. In this work, we investigated the two mass parameters-template and locus-specific amplification efficiencies-and used MLE (maximum likelihood estimation) and MCMC (Markov chain Monte Carlo) methods to obtain point estimates to calculate the total allelic product. The expected read counts for alleles were then calculated after proportioning some of the expected stutter product from the total allelic product. Due to preferential amplicon selection introduced by the sample purification beads, degradation is difficult to model from the aSTR outputs alone. Improved modeling of the locus-specific amplification efficiencies may mask the effects of degradation. Whilst this model could be improved by introducing locus specific variances in addition to locus specific priors, our results demonstrate the suitability of adapting Bright et al.'s allele peak height model for NGS-DNA profiles. This model could be incorporated into continuous probabilistic interpretation approaches for mixed DNA profiles.
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SciPy 1.0: fundamental algorithms for scientific computing in Python
Nature Methods · 2020 · 37.9K citations · Full text