familial dna searching - technology to provide investigative leads
TRANSCRIPT
Arthur J. Eisenberg, Ph.D., Professor and Chairman Dept. of Forensic and Investigative Genetics Co-Director UNT Center for Human Identification [email protected]
Familial DNA Searching - Technology to Provide Investigative Leads
COmbined DNA Index System
State CODIS Initiatives
ALL CONVICTED OFFENDER LEGISLATION 1999 – 5 states 2003 – 27 states 2008 – 42 states 2011 – 50 states
ARRESTEE LEGISLATION 1999 – 1 state 2006 – 7 states 2012 – 26 states
What is a Database?
• A database is an organized file or files of data that can be searched to retrieve information.
• DNA databases compare profiles derived from evidentiary samples to a database of DNA profiles obtained from known individuals to provide law enforcement agents with investigative leads*
• The FBI Laboratory's Combined DNA Index System (CODIS) blends forensic science and computer technology into an effective tool for solving crimes.
• CODIS enables federal, state, and local crime labs to exchange and compare DNA profiles electronically, thereby linking crimes to each other and to convicted offenders.
CODIS Mission
CODIS Architecture
National
LDIS Houston PD
LDIS Bexar County CL
CalDOJ
LDIS SWIFS Dallas
DPS
NDIS
SDIS
LDIS
California Texas
FDLE
Florida
• DNA profile entry and management: the function dealing with the database DNA profiles
• Searching: the function allowing a search of database DNA profiles
• Match management: the function managing search results
• Statistical calculations: Popstats function enabling laboratory personnel to calculate profile statistics based upon population frequency data
Primary Functions of CODIS Software
CODIS INDICES • OFFENDER
• Convicted Offenders • Arrestee
• FORENSIC • Forensic Crime Scene Samples
• MISSING PERSONS • Unidentified Human Remains • Missing Persons Direct Reference Samples
(tooth brush, hair brush, baby teeth, etc.) • Family Reference Samples
CODIS DNA Profile 1) ORI = DCFBIWAD7
FBI Laboratory Wash. DC Div.7 2) Specimen ID # MD060215039Q4M
MD, 2006, February 15 Case# 39 Question Specimen 4 Male Fraction
3) STR Profile 11,11; 12,12; 12,13; 10,20; 29,30; 16,18; 12,13; 09,11; 11,15; 23,24; 06,9.3; 08,08; 17,19; X, Y
4) Analyst Identifier = JCL This is the only information sent to the
National Level NDIS
Standard Database Search
• Search for offender profile(s) that matches all alleles of the forensic profile at all loci
Forensic profile
Offender profile – 1 Offender profile – 2 Offender profile – 3 Offender profile – 4 …
CRIME SCENE Database
Partial Match
• High stringency match • All alleles are “matched”
• Moderate stringency match • Allows for allele drop-out (primer binding,
DNA quality, or mixture) • AB -> AA or BB • AA -> A? (? is NOT A)
• Low stringency match • At least one allele in common or IBS≥1 (i.e., it
includes AB -> AC)
Examples
Target Offender Match IBS
11,12 11,12 High 2
10,10 10,10 High 2
17,17 17, X Moderate 1
18,18 18,19 Moderate 1
12,13 12,18 Low 1
18,20 18,19 Low 1
Database Search – Perfect Match
Locus Crime Scene Offender D3S1358 15,16 15,16 vWA 18,18 18,18 FGA 21,22 21,22 D8S1179 13,14 13,14 D21S11 29,30 29,30 D18S51 14,17 14,17 D5S818 11,12 11,12 D13S317 11,12 11,12 D7S820 10,11 10,11 CSF1PO 11,12 11,12 TPOX 8,11 8,11 TH01 6,9.3 6,9.3 D16S539 11,12 11,12
Familial Searching
• Familial searching is an attempt to detect potential relatives of a forensic profile in any specified database
Forensic profile
Offender profile – 1 Offender profile – 2 Offender profile – 3 Offender profile – 4 …
Similarity: forensic and OP-1 Similarity: forensic and OP-2 Similarity: forensic and OP-3 Similarity: forensic and OP-4 …
Rank the offender profiles by similarity
CRIME SCENE Database
Select the top candidates for further investigation
Offender profile – 2 Offender profile – 1 Offender profile – 4 Offender profile – 3 …
Database Search – No Exact Match However a Suspect with Many Similarities
Locus Crime Scene Suspect D3S1358 15,16 15,20 vWA 17,18 17,18 FGA 19,22 21,22 D8S1179 13,15 13,14 D21S11 29,30 29,30 D18S51 14,15 14,17 D5S818 11,11 11,12 D13S317 11,12 11,12 D7S820 11,11 10,11 CSF1PO 11,13 11,12 TPOX 8,11 8,11 TH01 6,9.3 6,9.3 D16S539 11,13 11,12
Partial Match and Kinship • The more similar the profiles are, the higher the probability
of kinship • Parent-child:
• 100% chance that parent-child share at least one allele
• Full-Sib: • 25% chance that two full-sibs share both alleles • 50% chance that two full-sibs share only one allele • 25% chance that two full-sibs share no alleles
• Unrelated: • The chance that two unrelated persons share at least
one allele at a locus is <40%, on average
Two Sexual Assault Cases in which the DNA profile from the male fraction of the vaginal swabs collected from both victims was searched within CODIS and no matches were made against either the Offender Database or the Forensic Crime Scene Database
Two Brutal Sexual Assault Cases That Occurred in Texas
Police obtained information which suggested that the individual who committed these two brutal rape/ homicide cases may be related to an individual who had been previously associated with a prior sexual assault case.
Two Brutal Sexual Assault Cases That Occurred in Texas
DNA Typing Results Evidence From Three Sexual Assault Cases
L33 L33 was a profile from a previously convicted rapist
L17 & L20 was a profile from murdered sexual assault victims
Ordered Genotypes
(X, Y) IBS
Joint Probabilities: Pr(X,Y| Φi)
Φ2 Φ1 Φ0
AiAi, AiAi 2
AiAi, AjAj 0 0 0
AiAi, AiAj 1 0
AiAi, AjAk 0 0 0
AiAj, AiAj 2
AiAj, AiAk 1 0
AiAj, AkAl 0 0 0
Joint Genotypic Probabilities
Φ0: IBD=0, Φ1: IBD=1, Φ2: IBD=2, and Φ0 + Φ1 + Φ2 =1. Ai, Aj, Ak and Al are alleles at the locus with allele frequencies pi, pj, pk, and pl, respectively. IBS is Identity-By-State. θ is the population substructure parameter.
2 (1 )i i ip p pθ+ − [ (1 )][2 (1 )]1
i i ip p pθ θ θ θθ
+ − + −+
[ (1 )][2 (1 )][3 (1 )](1 )(1 2 )
i i i ip p p pθ θ θ θ θ θθ θ
+ − + − + −+ +
(1 ) [ (1 )][ (1 )](1 )(1 2 )
i j i jp p p pθ θ θ θ θθ θ
− + − + −
+ +(1 )[ (1 )]
1i j ip p pθ θ θ
θ− + −
+2(1 ) [ (1 )][2 (1 )]
(1 )(1 2 )i j i ip p p pθ θ θ θ θ
θ θ− + − + −
+ +22(1 ) [ (1 )](1 )(1 2 )
i j k ip p p pθ θ θθ θ
− + −
+ +
2 (1 )i jp p θ− (1 )[( )(1 ) 2 ]1
i j i jp p p pθ θ θθ
− + − +
+
4(1 ) [ (1 )][ (1 )](1 )(1 2 )
i j i jp p p pθ θ θ θ θθ θ
− + − + −
+ +2(1 )
1i j kp p p θ
θ−
+
24(1 ) [ (1 )](1 )(1 2 )
i j k ip p p pθ θ θθ θ
− + −
+ +34(1 )
(1 )(1 2 )i j k lp p p pθ
θ θ−
+ +
DNA Typing Results Evidence From Three Sexual Assault Cases
L33
The genetic results are consistent with a familial relationship between the individual who contributed item L-33* and the individual who contributed items L-17* and L-20*. The individual who contributed the DNA obtained from sample L-33* cannot be excluded as the full sibling of the unknown individual who contributed the DNA obtained from samples L-17* and L-20*. The most likely familial relationship supported by the genetic results is a full sibling.
Did The Brother Do It?
It is 2,319 times more likely to have observed the genetic results for samples L-33*, L-17*, and L-20* under the scenario that the individual who contributed the DNA recovered from sample L-33*, and the individual who contributed the DNA recovered from samples L-17* and L-20* are full siblings, as compared to the scenario that the individual who contributed the DNA recovered from sample L-33*, and the individual who contributed the DNA recovered from the samples L-17* and L-20* are two unrelated individuals of the Hispanic population group.
Did The Brother Do It?
With an assumption of a prior probability of 0.5 (this indicates a 50% prior probability that the contributors were full siblings and a 50% prior probability that the two contributors are unrelated, this represents a neutral prior probability), there is a 99.95% probability that the contributor of item L-33* and the contributor of items L-17* and L-20* are full siblings as compared to two unrelated individuals of the Hispanic population group.
Did The Brother Do It?
The suspect in the two rape/homicide cases was located in Mexico. Law enforcement agents went into Mexico and followed their suspect. A bottle which had been discarded by the suspect was recovered and a DNA profile was obtained. The DNA profile obtained matched the DNA profiles obtained from evidence samples L-17* and L-20. The Police Department worked with the United States Attorney’s Office and the State Department in order to have the suspect extradited to the United States to stand trial for Capitol Murder.
Did The Brother Do It?
Familial Searching Premise and Definition
Premise • Assume that a target STR DNA profile is in hand, and its
source is being investigated • Further assume that there is no exact match of this target
profile in a DNA database (such as the offenders’ database in CODIS or similar databases)
Definition • Familial search constitutes the attempt to detect potential
relatives of one or more records in the database searched, which show enough similarity with the target profile (with specific measures of similarity)
• The advent of DNA-STR technology and the development of DNA databases have allowed investigators to search for near genetic matches to help solve crimes committed by relatives of people in the database
• Familial DNA Database Searches are based on the fundamental principle that DNA profiles of people who are related are likely to contain similarities
Familial Searching is ….
• Siblings, parents, and in some cases even uncles, aunts and cousins, can be linked to crimes because their relative’s DNA closely resembles DNA found at a crime scene
• Typically Familial DNA database searches are best for two lines of inquiry: • the identity of an individual who could be a
sibling of the offender • the identity of an individual who could be the
offender’s parent or child
Familial Searching is ….
US Bureau of Justice Statistics
• Correctional populations in United States 1996 • at least 42.8% of jail inmates had close
biological relatives (i.e., father, mother, brother, sister, child) who were incarcerated
• about 36.5% inmates had full-sibs who had been incarcerated
• 22.8% had parents or children incarcerated
• Paternity or Maternity Testing • Baby Abandonments (Dumpster Babies) • Products of Conception • Identification of Missing Persons and
Human Remains
Familial Searching is Not a New Concept or Technique
Parent-Child relationship testing
AB
AC
1
2
P(E | H )PI P(E | H )
=
P(E|H1)
• Evidence (E) • Alleged father’s genotype “AC” • Child’s genotype “AB”
• Hypothesis (H1) • The alleged father is the biological
father
AB
AC
P(E|H1)
• Genotype freq. of the alleged father = Pr(AC)
• Alleged father transmit one allele “A” to the child = 1/2
• Allele “B” is from a random person = Pr(B)
• P(E|H1) = Pr(AC) × 1/2 × Pr(B)
A B
AC
Random Person
P(E|H2)
• Evidence (E) • Alleged father’s genotype “AC” • Child’s genotype “AB”
• Hypothesis (H2) • The alleged father is NOT the biological
father • These two persons are unrelated
AB
AC
P(E|H2)
• Genotype freq. of the alleged father = Pr(AC)
• Both alleles of the child are not transmitted from the alleged father = Pr(AB)
• P(E|H2) = Pr(AC) × Pr(AB)
AB
AC
Paternity Index for a Parent Offspring
1
2
( | ) ( | )
Pr( ) 1/ 2 Pr( ) Pr( ) Pr( )
P E HPIP E H
AC BAC AB
=
× ×=
×
1/ 2 Pr( ) =2 Pr(A) Pr( )
BB
×× ×
1 =4Pr(A)
• The victim, a 24 year old waitress was walking home along Ryde seafront at about midnight following her shift at a fast food outlet on 4 August, 1990
• A man approached her from behind, put his T-shirt over her head and attacked her
• The police had no suspects and had exhausted all leads.
• Then advancements in technology enabled the development of a DNA profile from material found at the crime scene (in 2004)
• Searched the national DNA database and there were no “matches.”
Familial Searching United Kingdom case
• The breakthrough came when Davison’s daughter gave a DNA sample after she was cautioned for an assault in 2006.
• By familial searching an investigative lead was developed between the crime scene profile and his daughter’s profile.
• Davison voluntarily provided a sample which showed a match and he was charged.
• Davison, 52, of Ryde, was convicted of rape in January and jailed for eight years at Portsmouth Crown Court.
• Davison's victim said: "Eight years in prison is a good result but no sentence will undo the harm I have suffered. At least now I can hope to move forward.”
Familial Searching United Kingdom case
Familial Searching United Kingdom case
Keith Davison was placed on a sex offenders register for life
Craig Harman - a brick was thrown through the windshield of the victim’s truck from a bridge above a highway, causing the victim to suffer a fatal heart attack. • DNA from the brick was checked against the UK
National Database but there was no exact match. Twenty-five people with similar DNA were located in the database and the defendant's relative was top of the list.
• A voluntary DNA sample from Harman was found to be a perfect match and, in the face of the evidence, he pleaded guilty to manslaughter.
• This was the first conviction via familial searching of a database (2003-2004)
http://www.denverda.org/dna/Familial_DNA_Database_Searches.htm
Familial Searching
• First solved case in Denver and one of a very few in US
• Break-in of two cars in February 2008 • No DNA match in CODIS • Search found a close but not exact
DNA “match” from blood found at an auto burglary
• His brother’s DNA helped identify Luis Jaimes-Tinajero
• He plead guilty to one count of criminal trespass for both thefts
• This was the sixth potential familial lead (first five did not lead to any suspects)
Familial Searching Denver, Colorado November 17, 2009
Good strategies need to be developed to avoid inefficient investigations
(1) Precise measures
(2) Number of candidates
Familial Search Can Work
Assumptions
• Single source profile • No more than two alleles at each locus • No mixture
• No genotyping errors • No allele drop out • No allele drop in
Pairwise Kinship Analysis
• Identity by State (IBS) – count the number of shared alleles
Forensic Offender IBS (10, 12) (11, 13) 0 (11, 12) (11, 13) (11, 12) (11, 12)
1 2
Pairwise Kinship Analysis
• Likelihood ratio (LR) or Kinship Index (KI) – same method as paternity testing • Kinship hypothesis (Hk): the two individuals
are related by the given relationship • Non-Kinship hypothesis (Hnk): the two
individuals are unrelated
= ) H | P(E
) H | P(E
nk
k KI
Pairwise Kinship Analysis
One million simulation results with Caucasian population data and 13 CODIS core STRs Jianye Ge et al. Choosing relatives for missing person identification, Journal of Forensic Science, 2011 Jan;56
Familial Searching Strategies
• Number of shared allele or IBS based
• Likelihood Ratio (LR) or Kinship Index (KI) based • LR or KI
False Positives and False Negatives
Decision True State
Unrelated Related
Unrelated Correct decision False negative (Type 2 Error)
Related False positive (Type 1 Error) Correct decision
False Positive
• In all unrelated pairs, a proportion of pairs may be falsely associated as related
Distribution of unrelated Threshold
False positive
False Negative
• In all related pairs, a proportion of pairs may be falsely classified as unrelated
Distribution of related Threshold
False negative
False Positive and False Negative
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
Related Unrelated
Familial Searching Strategies Based on IBS
• Count the number of shared alleles or loci between two profiles
• Pros • Population ancestry is not considered • Simple and easy to implement
• Limitations • Allele frequency information is not
exploited
Policy Based on IBS – Counting IBS • California policy: at least 15 shared alleles • Simulation results (13 Caucasian CODIS loci):
– False negative: 18.4% for parent-child; 17.8% for full-sib
– False positive: 0.45%; 4,500 potential hits in 1 million unrelated profiles
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
Prop
ortio
n
Number of Share Alleles
UnrelatedFullSibParentChild
Policy Based on IBS – Low stringency • Some other states (e.g., Florida, Nebraska, Oregon, Washington)
require at least one allele shared at all available loci • Simulation study (mutation rates from AABB annual report)
– False negative: >99% for parent-child; 76.0% for full-sib – False positive: 0.077% (i.e., 770 in a million unrelated profiles)
0.00
0.20
0.40
0.60
0.80
1.00
0 1 2 3 4 5 6 7 8 9 10 11 12 13
Prop
ortio
ns
Number of loci with at least one allele shared
Unrelated
Full-Sib
Parent-Child
Policy Based on IBS – Moderate stringency • Moderate stringency has “little useful probative value” in
familial searching – SWGDAM recommendations – Majority of both related and unrelated profiles are
excluded
0
0.05
0.1
0.15
0.2
0.25
0.3
0 1 2 3 4 5 6 7 8 9 10 11 12 13
Prop
ortio
n
Number of loci with moderate strigency match
Unrelated
FullSib
ParentChild
IBS Based Polices
• Counting IBS – Need to define a threshold that balances false positive
and false negative rates
• Low stringency – Good for searching parent-offspring – Barring mutation
• Moderate stringency
– Not practical for familial searching
Familial Searching Policies Based on Kinship Index (KI)
• Compare two alternative hypotheses – Kinship hypothesis (Hk): the two individuals are related as the
given relationship – Non-Kinship hypothesis (Hnk): the two individuals are not related
• Pro – Uses allele frequency information effectively
• Limitations – Dependant on the population data; i.e., the KI value would vary
among populations
0,1,2
0,1,2
Pr( , | ) Pr( | )
Pr( , | ) Pr( | )
i ii
i ii
X Y RelationshipKI
X Y Unrelated=
=
Φ Φ=
Φ Φ
∑∑
KI Distributions
• Distributions of the KI values depend on the STRs chosen, but not on the database size
• KI=1,000 or 10,000 (i.e., log10(KI) = 3 or 4) might be a good measure for the 13 CODIS loci to balance the false positive and false negative detection rates.
0
10000
20000
30000
40000
50000
-10 -8 -6 -4 -2 0 2 4 6 8 10 12 14
Log10(KI)
True Full-Sib
Unrelated identified as Full-Sib
Unrelated identified as Parent-Child
816,696
True Parent-Child
Effect of Population Substructure • Population substructure (θ) has a slight affect on
the likelihood ratio calculations • The differences of the LRs with θ=0 or θ=0.01 are
within 10-fold in 99% of the cases
0
2000
4000
6000
8000
10000
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Coun
ts
(KI with θ=0)/(KI with θ=0.01)
Parent-Child
Full-Sib
Rare Alleles
• It may be difficult to define how rare a “rare” allele should be
• Generally, the weights of rare alleles are taken into account in the KI calculation
• Actual power of rare alleles may not be fully exploited for familial searching, because some rare alleles may be assigned as greater or less than the limits of the allelic ladder (e.g., >20 or <5) or limited by the size of the database
Joint Use of IBS and KI
• Unrelated identified as full-sib
• Joint Use of IBS and KI decreases the false positive rates • IBS ≥ 16: 1,116 out of 1 million; KI ≥ 1,000: 93 out of 1 million • Joint: 75 out of 1 million (exclude 93.3% false hits from IBS and 19.4% false hits from KI)
Log10(KI) IBS
Sum ≤11 12 13 14 15 16 17 18 19
<=0 897655 54299 18383 2512 65 0 0 0 0 972914 (0,1] 923 4027 8601 6652 1593 101 0 0 0 21897 (1,2] 18 119 620 1502 1580 518 62 0 0 4419 (2,3] 1 1 26 83 206 228 120 11 1 677 (3,4] 0 0 0 4 14 29 19 19 1 86 (4,5] 0 0 0 0 0 1 1 1 1 4 (5,6] 0 0 0 0 0 0 1 1 1 3 Sum 898597 58446 27630 10753 3458 877 203 32 4 1000000
Rank of the True Hit • A true relative may be at the bottom of the list,
or even not on the candidate hit list • The position of a true relative (if present in the
database) in the candidate hit list depends on the database size and the frequencies of specific alleles in the profiles
• Example: – A full-sib pair is expected to have about 16.6 shared
alleles and a KI of roughly 2,500 for 13 CODIS loci – The expected rank of the true full-sib hit: >100,
with a database containing 1 million unrelated profiles
Needs for Higher Accuracy with Familial Searching • More autosomal STR loci
– Both false negative and false positive rates are reduced with extra STR loci
– The expected rank of the true full-sib hit with 15 STRs is around 6, with a database containing 1 million unrelated profiles
Identifications Means with 13 STRs Means with 15 STRs*
IBS Log10(KI) IBS Log10(KI) FS FS 16.5996 3.4012 19.064 3.9999 PC PC 15.8409 4.0833 18.2018 4.8119 UN FS 8.7088 -2.8043 9.8483 -3.3029 UN PC 8.7122 -15.5829 9.8431 -19.0476
(15 STRs*) 13 CODIS STRs, D2S1338, and D19S433
Strategy Based on IBS – Counting IBS
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
Prop
ortio
n
Number of Share Alleles
Unrelated
FullSib
ParentChild
Florida, IBS≥21
25% Parent Child share 15 alleles
False Rates by IBS Method
strategy False positive False negative
Unrelated Parent-Child Full-Sib
IBS≥14 1.53% 3.8% 8.9%
IBS≥15 0.46% 18.4% 17.8%
IBS≥16 0.12% 43.3% 31.1%
IBS≥17 0.024% = 4.2×10-4 69.0% 47.7%
IBS≥18 0.0042% = 4.2×10-5 86.9% 64.8%
IBS≥19 0.00059% = 5.9×10-6 95.7% 79.6%
IBS≥20 0.000067% = 6.7×10-7 98.9% 90.1%
IBS≥21 0.000006% = 6.0×10-8 99.8% 96.0%
Familial Searching Strategies: Based on Kinship Index (KI)
• Compare the likelihoods given two alternative hypotheses, related or unrelated
• Pros • Uses allele frequency information more
effectively • Limitations
• Dependant on population data; i.e., the KI value would vary among populations
KI Distributions (1 million simulations)
0
10000
20000
30000
40000
50000
-10 -8 -6 -4 -2 0 2 4 6 8 10 12 14
Log10(KI)
True Full-Sib
Unrelated identified as Full-Sib
Unrelated identified as Parent-Child
816,696
True Parent-Child
False Rates of KI Thresholds
Strategy
False Positive False Negative Unrelated identified as True
Parent-Child True
Full-Sib Parent-Child Full-Sib
KI≥1,000; Log10(KI)=3 0.0132% 0.0093% 14.1% 42.5%
KI≥10,000; Log10(KI)=4 0.0014% 0.0007% 49.4% 63.2%
KI≥100,000; Log10(KI)=5 0.0001% 0.0003% 81.9% 80.2%
KI≥200,000;Log10(KI)=5.3 <0.0001% <0.0001% 87.8% 84.2%
KI≥1,000,000; Log10(KI)=6 <0.0001% <0.0001% 95.7% 91.2%
Candidate List
• How many candidate profiles to select for further testing? • Resources • Budget • High profile case? • Required confidence of the association
Confidence Curves database with 1 million unrelated; KI
Confidence curves database with 100k unrelated; KI
• Y chromosome • KI ≈ 1,000 to 10,000 with 16 Y chromosome STR loci • Dependant on database size and population
• Mitochondrial DNA • KI ≈ hundreds to 1,000 with HVI and HVII
• The true relative hit with 13-15 CODIS STRs and Y-STR/mtDNA is expected at the top of the list, with a database containing 1 million unrelated profiles
Pr( | ) 1Pr( | )
Evidence same lineageKIEvidence different lineage haplotype frequency
= =
Use of Lineage Markers in Familial Searching of Databases
California Strategy
• California accepts up to 168 familial matches based on autosomal STRs and then tests these candidates with Y-STRs. The “168” is based on two 96-well plates being used • 84 for each plate • Ladders and controls
• Minnesota: 152
Grim Sleeper Case • The known killings began in 1985 in South Los Angeles,
California. The Grim Sleeper took a 14 year hiatus after his last murder in 1988 but began murdering again in 2002. His last confirmed murder was in January 2007.
• DNA samples of the perpetrator were collected from his victims, but no direct match was found in the State or National CODIS database.
• In 2008, the LAPD ran a familial DNA search against their State CODIS database; that failed to provide any investigative leads.
Grim Sleeper Case • Police had been unable to find an exact match between
DNA found at the crime scenes associated with the Grim Sleeper and any of the profiles in California's DNA profile database.
• Thus, police searched the database to try to find stored profiles that demonstrated sufficient similarity to the profile from the crime-scene evidence to allow police to infer a familial relationship between the person who left the DNA at the crime scenes and the similar profile stored in the database.
Grim Sleeper Case • In 2010, police eventually located a similar DNA
belonging to, Christopher Franklin, who was the son of Lonnie David Franklin.
• Christopher Franklin had been convicted of a felony weapons charge, and his DNA profile was put into CODIS.
• With the potential familial association, detectives then used a piece of discarded piece of pizza to obtain a DNA sample from Lonnie David Franklin that matched the evidentiary samples obtained from his multiple victims.
Grim Sleeper Case • Franklin had a criminal record dating back to 1989. He
was convicted of two charges of stolen property, one charge of misdemeanor assault, and one charge of battery. He served time for one of the charges of stolen property.
• Law enforcement missed multiple opportunities to catch Franklin because his DNA was never collected. In 2003, he was convicted of a felony and was serving three years of supervised probation. When he was on probation, his DNA was supposed to enter the DNA database.
Grim Sleeper Case • In 2004, voters approved of Proposition 69. The law states
that DNA must be collected for all people charged with a crime. It also requires the expansion of the DNA database. Authorities collected and sorted through thousands of DNA samples.
• On July 2005, Franklin was on unsupervised probation. During that time, Franklin's DNA never entered into the system. Probation officers did not collect DNA samples from people that are on unsupervised probation between the periods of November 2004 and August 2005.
Grim Sleeper Case
Lonnie Franklin was charged with 10 murders and 1 attempted murder dating back to 1985
Suggested Searching Strategy • Use high thresholds first to generate a
manageable list • IBS ≥ 21 • KI ≥ 1,000,000 = 106
• Reduce the threshold step by step • IBS 20, 19, 18, 17, … • KI ≥ 105, 104, 103 , …
• Use KI as the primary threshold criterion, because KI is more informative than IBS
• Use “Minimum KI” option for multiple KI values
Familial Searching Software
Familial Searching Software
The University of North Texas Health Science Center
Department of Forensic and Investigative Genetics
• Faculty Bruce Budowle* John Planz Ranajit Chakraborty* Rhonda Roby Arthur Eisenberg* Joseph Warren Jianye Ge* Harrell Gill-King
•Institute of Applied Genetics • Center for Human Identification • Center for Computational Genomics • Center for BioSafety and BioSecurity
Center for Forensic Excellence 2013 Schedule
Center for Forensic Excellence 2013 Schedule
Professor and Chairman Dept. of Forensic and Investigative Genetics
Co-Director UNT Center for Human Identification, Institute of Investigative Genetics
Director DNA-Prokids USA University of North Texas Health Science Center
Fort Worth, Texas USA 817 735-0555
Arthur J. Eisenberg, PhD
