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TrueAllele® Interpretationof DNA Mixture Evidence
99thth International Conference on International Conference onForensic Inference and StatisticsForensic Inference and Statistics
August, 2014August, 2014Leiden University, The NetherlandsLeiden University, The Netherlands
Mark W Perlin, PhD, MD, PhDMark W Perlin, PhD, MD, PhDCybergenetics, Pittsburgh, PACybergenetics, Pittsburgh, PA
Cybergenetics © 2003-2014Cybergenetics © 2003-2014
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TrueAllele® Casework
ViewStationUser Client
DatabaseServer
Interpret/MatchExpansion
Visual User InterfaceVUIer™ Software
Parallel Processing Computers
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On the Origin of TrueAllele
1993 @ CMU: stutter deconvolutionAmerican Journal of Human Genetics
1999 @ Cybergenetics: mixture deconvolutionJournal of Forensic Sciences
Scope: STR mixtures, degraded, kinship, database
Data: (respect) use everything, add nothingObjective: never consider suspect referenceGeneral: same for evidentiary & investigative
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Variation Under Domestication8
12locus
peak size
peak
hei
ght
Hypothesis: evidence and suspect share a common
contributor
Data analysis:simple threshold
Single source DNA
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Variation Under Nature
10
13
8
12 victim
other
victim
other
Hypothesis: evidence and suspect share a common
contributor
Data analysis:patterns & variation
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Struggle for ExistenceLikelihood ratio (LR) requires genotype probability
LR = O( H | data)
O( H )
Σx P{dX|X=x,…} P{dY|Y=x,…} P{X=x}
ΣΣx,y P{dX|X=x,…} P{dY|Y=y,…} P{X=x, Y=y}=
Bayes theorem + probability + algebra …
genotype probability: posterior, likelihood & prior
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Natural Selection
Hierarchical Bayesian modelinduces a set of forces in a high-dimensional parameter space
Mixture weightvariables
Genotypevariables
• small DNA amounts• degraded contributions• K = 1, 2, 3, 4, 5, 6, ... unknown contributors• joint likelihood function
Hierarchicalmixture weightlocus variables
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Survival of the FittestMarkov chain Monte Carlo
Sample from the posterior probability distribution
Current state
Next state?
Transition probability = P{Next state}
P{Current state}
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Laws of Variation
Hierarchy of successive pattern transformations
Variance parameters
Hierarchical(e.g., customized for DNA template or locus)
Differential degradationMixture weightRelative amplificationPCR stutterPCR peak heightBackground noise
genotype
data
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Difficulties of the Theory
procedures & rules vs data-driven science
comfort in certainty vs tackling uncertainty
probability and likelihood ratioscan use all the data to
quantify uncertainty
What is the aim of Forensic Science?comfort vs truth
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Miscellaneous Objections
• too complex?• black box?• source code?• insufficient validation?
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Validation StudiesPerlin MW, Sinelnikov A. An information gap in DNA evidence interpretation. PLoS
ONE. 2009;4(12):e8327.
Perlin MW, Legler MM, Spencer CE, Smith JL, Allan WP, Belrose JL, Duceman BW. Validating TrueAllele® DNA mixture interpretation. Journal of Forensic
Sciences. 2011;56(6):1430-47.
Ballantyne J, Hanson EK, Perlin MW. DNA mixture genotyping by probabilistic computer interpretation of binomially-sampled laser captured cell populations: Combining quantitative data for greater identification information. Science &
Justice. 2013;53(2):103-14.
Perlin MW, Belrose JL, Duceman BW. New York State TrueAllele® Casework validation study. Journal of Forensic Sciences. 2013;58(6):1458-66.
Perlin MW, Dormer K, Hornyak J, Schiermeier-Wood L, Greenspoon S. TrueAllele® Casework on Virginia DNA mixture evidence: computer and manual
interpretation in 72 reported criminal cases. PLOS ONE. 2014;(9)3:e92837.
Perlin MW, Hornyak J, Sugimoto G, Miller K. TrueAllele® genotype identification on DNA mixtures containing up to five unknown contributors. Journal of Forensic
Sciences. 2015;in press.
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Sensitive
The extent to which interpretation identifies the correct person
101 reported genotype matches 82 with DNA statistic over a million
True DNA mixture inclusions
TrueAllele Casework on Virginia DNA mixture evidence: computer and manual interpretation in 72 reported criminal cases.
Perlin MW, Dormer K, Hornyak J, Schiermeier-Wood L, Greenspoon S PLoS ONE (2014) 9(3): e92837
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TrueAllele Sensitivity
11.05 (5.42)113 billion
TrueAllele
log(LR) match distribution
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Specific
The extent to which interpretation does not misidentify the wrong person
101 matching genotypes x 10,000 random references x 3 ethnic populations,
for over 1,000,000 nonmatching comparisons
True exclusions, without false inclusions
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TrueAllele Specificity
– 19.47
log(LR) mismatch distribution
0
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Reproducible
MCMC computing has sampling variation
duplicate computer runson 101 matching genotypes
measure log(LR) variation
The extent to which interpretation givesthe same answer to the same question
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TrueAllele ReproducibilityConcordance in two independent computer runs
standard deviation(within-group)
0.305
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Manual Inclusion MethodOver threshold, peaks become binary allele events
All-or-none allele peaks,disregard quantitative data
Allele pairs7, 77, 107, 127, 14
10, 1010, 1210, 1412, 1212, 1414, 14
Analyticalthreshold
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CPI Information
CPI6.83 (2.22)6.68 million
Combined probability of inclusion
Simplify data, easy procedure,apply simple formula
PI = (p1 + p2 + ... + pk)2
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Modified Inclusion Method
Stochasticthreshold
Higher threshold for human review
Analyticalthreshold
Apply two thresholds,doubly disregard the data
in 2010
in 2000
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Modified CPI Information
CPI6.83 (2.22)6.68 million
2.15 (1.68)140
mCPI
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Method Comparison
CPI
11.05 (5.42)113 billion
6.83 (2.22)6.68 million
2.15 (1.68)140
mCPI
TrueAllele
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Method Accuracy
KolmogorovSmirnov test
K-S p-value0.106 0.2150.561 1e-220.735 1e-25
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Invariant Behavior
Perlin MW, Hornyak J, Sugimoto G, Miller K. TrueAllele® genotype identification on DNA mixtures containing up to five unknown contributors.
Journal of Forensic Sciences. 2015;in press.
no significant difference in regression line slope
(p > 0.05)
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Sufficient Contributors
small negative slope valuesstatistically different from zero
(p < 0.01)
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Admissibility Hearings
• California• Pennsylvania• Virginia• United Kingdom• Australia
Appellate precedent in Pennsylvania
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Westchester, NY: Daughter RapeQuantitative peak heights at locus D16S539
peakheight
peak size
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How TrueAllele ThinksConsider every possible genotype solution
Explain thepeak pattern
Better explanationhas a higher likelihood
One person’s allele pair
Another person’s Another person’s allele pairallele pair
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Objective genotype determined solely from the DNA data.
Never sees a comparison reference.
Evidence Genotype
99.9%
0.02%0.08%
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DNA Match Information
Prob(evidence match)
Prob(coincidental match)
How much more does the child match the evidencethan a random person?
14.5x99.9%
6.9%
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Match Information at 15 Loci
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Likelihood Ratio Results
A match between the blanket and the child is 68 quadrillion times more probable than coincidence.
A match between the blanket and the father is33 quadrillion times more probable than coincidence.
Father pleaded guilty to rape and was sentenced to seven years in prison.
Young daughters spared further torment.
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Other Cases
Mixtures of family members • child rape • homicide • 3 person mixture • 5 person mixture
Over 200 case reports • Many states & countries
On-line in crime labs • California • Virginia • Middle East
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Investigative DNA DatabaseInfer genotypes, and then match with LR
World Trade Center disaster
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DNA Mixture Crisis: MIX05National Institute of Standards and Technology
Two Contributor Mixture Data, Known Victim
31 thousand (4)
213 trillion (14)
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DNA Mixture Crisis: MIX13
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DNA Mixture Crisis: USA
375 cases/year x 4 years = 1,500 cases320 M in US / 8 M in VA = 40 factor
1,500 cases x 40 factor = 60,000 inconclusive
1,000 cases/year x 4 years = 4,000 cases320 M in US / 8 M in NY = 40 factor
4,000 cases x 40 factor = 160,000 inconclusive
+ under reporting of DNA match statistics
DNA evidence data in 100,000 casesCollected, analyzed & paid for – but unused
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The Rule of Science & Law unworkable rules vs validated science
Why do we practice Forensic Science?
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