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A person's genotype 8, ACGT A genetic locus has two DNA sentences, one from each parent. 9 locus Many alleles allow for many many allele pairs. A person's genotype is relatively unique. mother allele father allele repeated word An allele is the number of repeated words. A genotype at a locus is a pair of alleles.
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When Good DNA Goes Bad
International Conference onInternational Conference onForensic Research & TechnologyForensic Research & Technology
October, 2012October, 2012Chicago, IllinoisChicago, Illinois
Mark W Perlin, PhD, MD, PhDMark W Perlin, PhD, MD, PhDCybergenetics, Pittsburgh, PACybergenetics, Pittsburgh, PA
Cybergenetics © 2003-2012Cybergenetics © 2003-2012
DNA mixture evidence
Virginia reevaluates DNA evidence in 375 casesJuly 16, 2011
“Mixture cases are their own little nightmare,” says William Vosburgh, director of the D.C. police’s crime
lab. “It gets really tricky in a hurry.”
“If you show 10 colleagues a mixture, you will probably end up with 10 different answers”
Dr. Peter Gill, Human Identification E-Symposium, 2005
A person's genotype
8, 91 2 3 4 5 6 7 8
ACGT
1 2 3 4 5 6 7 8
A genetic locus has two DNA sentences,one from each parent.
9
locus
Many alleles allow formany many allele pairs. A person's genotype is relatively unique.
motherallele
fatherallele
repeated word
An allele is the numberof repeated words. A genotype at a locusis a pair of alleles.
DNA mixture genotypes
13 14
16 18
17 20
Allele size
DN
A a
mou
nt
First contributor
Second contributor
Third contributor
M. W. Perlin. "DNA identification science," In: Wecht CH, editor. Forensic Sciences. Albany, NY: LexisNexis® Matthew Bender®; 2012; Chapter 37C.
Good DNA evidence data
First contributor
Second contributor
Third contributor
Misinterpreted, data goes bad
Below threshold, data unused
Above threshold, peak heights are ignored
TrueAllele solves mixtures
13 14
16 18
17 20
First contributor
Second contributor
Third contributor
Objective & thorough;DNA match statistic
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.
Commonwealth v. LyonsLocation:
Crime:Evidence:
True information:Human guess:
Reason:Outcome:
Eastern United StatesMurderSweatshirt124Degraded mixtureDeath penalty
-15 -12 -9 -6 -3 0 3 6 9 12 15
369
Hum
an
Information
Commonwealth v. FoleyEastern United StatesMurderVictim's fingernails114Minor 7% DNA mixtureLife in prison
-15 -12 -9 -6 -3 0 3 6 9 12 15
369
Information
Location:Crime:
Evidence:True information:
Human guess:Reason:
Outcome:
Hum
an
M. W. Perlin, "The Blairsville slaying and the dawn of DNA computing," in Death Needs Answers: The Cold-Blooded Murder of Dr. John Yelenic,
A. Niapas, New Kensington, PA: Grelin Press, 2012.
The Queen v. ShiversNorthern IrelandMurder, terrorMobile phone90 (inconclusive)Low DNA amount25 years in prison
-15 -12 -9 -6 -3 0 3 6 9 12 15
369
Information
Location:Crime:
Evidence:True information:
Human guess:Reason:
Outcome:
Hum
an
M. W. Perlin & J. Galloway, "Computer DNA evidence interpretation in the Real IRA Massereene terrorist attack," Evidence Technology Magazine. 2012;10(3):20-23.
State v. Diggins
-15 -12 -9 -6 -3 0 3 6 9 12 15
369
Information
Location:Crime:
Evidence:True information:
Human guess:Reason:
Outcome:
Hum
an
Commonwealth v. Doe
-15 -12 -9 -6 -3 0 3 6 9 12 15
369
Information
Location:Crime:
Evidence:True information:
Human guess:Reason:
Outcome:
Hum
an
Quantitative interpretation:accurately excludes
suspect
othervictim?
Penta E locus
Allele length
Pea
k he
ight
Matchinformation
Computer -0.25
Human misinterpretationcan falsely implicate
Penta E locus
Allele length
Pea
k he
ight
Matchinformation
Computer -0.25
Human says nothing
ThresholdX X XX X
Computer reinterpretation,charges were dropped
information human computer
suspect 2 18
other 2 18
victim 2 0
Commonwealth v. Brown
-15 -12 -9 -6 -3 0 3 6 9 12 15
369
Information
Location:Crime:
Evidence:True information:
Human guess:Reason:
Outcome:
Hum
an
State v. SmithWestern United StatesAssault with weaponGun-10 (inconclusive)MixtureStill in prison
-15 -12 -9 -6 -3 0 3 6 9 12 15
369
Information
Location:Crime:
Evidence:True information:
Human guess:Reason:
Outcome:
Hum
an
DNA database exoneration?
Computer-inferredevidence genotype
Post-conviction testInformation < 0
The right person?Information ~ 9
10 million offendersCan’t use CODIS –Good data gone bad
M. W. Perlin, "Investigative DNA databases that preserve identification information," American Academy of Forensic Sciences 64th Annual Meeting, Atlanta, GA, 2012.
TrueAllele v. People
-15 -12 -9 -6 -3 0 3 6 9 12 15
369
Information
Hum
an
• Good DNA data can make identifications• Computer can determine true information• Human review does not always correlate• And then, good DNA data goes bad
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