How TrueAllele ® Works (Part 2) Degraded DNA and Allele Dropout Cybergenetics Webinar November, 2014 Mark W Perlin, PhD, MD, PhD Cybergenetics, Pittsburgh,

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Presentation transcript:

How TrueAllele ® Works (Part 2) Degraded DNA and Allele Dropout Cybergenetics Webinar November, 2014 Mark W Perlin, PhD, MD, PhD Cybergenetics, Pittsburgh, PA Cybergenetics ©

Commonwealth v. Lyons homicide: DNA mixture evidence Victim's blood spatter pulsating spray from severed carotid artery 70% victim 30% other

Copy DNA with PCR Copy intact DNA

Degraded DNA Can’t copy broken DNA break

Longer molecules copy less With degradation, a longer DNA molecule has a greater chance of having a break

Break density & copy probability the break density p = Pr(break at a nucleotide) q = Pr(no break at a nucleotide) = 1 – p q n = Pr(no break in n nucleotides) the copy probability

Decay factor λ pqλ n 1/ ∞ copy probabilitybreak density

DNA decay curve DNA size Observed DNA With degradation, a longer DNA molecule makes fewer DNA copies half length signal decay λ =.0035 n 1/2 = 200 (100 bp)

Reduced match information Degraded DNA Lower peak height Greater data variation More genotype uncertainty Diffused genotype probability Reduced match information

Differential mixture degradation computer separates decay curves

Affects mixture weight, genotypes

Degraded mixture separation Degraded other DNA Victim DNA likelihood priorposterior

Mixture weight separation w 2 = 30%w 1 = 70%30:70 vs 15:85 likelihood priorposterior

likelihood priorposterior Genotype separation

Information comparison A match between the suspect and the evidence is a trillion times more probable than coincidence. (TrueAllele solving for degradation) A match between the suspect and the evidence is a billion times more probable than coincidence. (TrueAllele not solving for degradation) Combined probability of inclusion of 42 thousand. (Human review with thresholds)

Likelihood ratio 9 ban 12 ban

Hierarchical mixture modeling template weight locus weights WkWk W k,1 W k,2 W k,N … k th contributor W0W0 prior probability experiment data d k,1 d k,2 d k,N …

Allele dropout 713 An allele present in a contributor genotype is not seen as a peak in the STR data. ?

Genotype modeling Compare patterns: fixed data vs possible explanations

Faithful data 2022

Genotype & LR 22

Imbalanced data 1012

Genotype & LR 1.5

Drop out data 713

Genotype & LR.35

TrueAllele result, but no CPI log(LR) Count YESNO Locus free of drop-out or imbalance? (0.664) N = 68 – (0.346) N = 29 How inclusion interpretation of DNA mixture evidence reduces identification information. Perlin MW, Dormer K, Hornyak J, Meyers T, Lorenz, W, American Academy of Forensic Sciences, Washington, DC, 2013.

Separating truth from noise Simple two person mixture, 10% minor contributor An investigation of software programs using “semi-continuous” and “continuous” methods for complex DNA mixture interpretation. Coble M, Myers S, Klaver J, Kloosterman A, Leiden University, The Netherlands, 9th International Conference on Forensic Inference and Statistics, 2014.

Separating truth from noise Simple two person mixture, 10% minor contributor Threshold and drop parameter An investigation of software programs using “semi-continuous” and “continuous” methods for complex DNA mixture interpretation. Coble M, Myers S, Klaver J, Kloosterman A, Leiden University, The Netherlands, 9th International Conference on Forensic Inference and Statistics, 2014.

How TrueAllele Works Part 1, 16-Oct-2014 Genotype modeling and the likelihood ratio Part 2, 20-Nov-2014 Degraded DNA and allele dropout Part 3, 18-Dec-2014 Kinship, paternity and missing persons