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Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Dec 24, 2015

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Page 1: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Forensic Statistics

From the ground up…

Page 2: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Basics

• Interpretation

• Hardy-Weinberg equations

• Random Match Probability

• Likelihood Ratio

• Substructure

Page 3: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Three Types of DNA Forensic Issues

• Single Source: DNA profile of the evidence sample providing indications of it being of a single source origin

• Mixture of DNA: Evidence sample DNA profile suggests it being a mixture of DNA from multiple (more than one) individuals

• Kinship Determination: Evidence sample DNA profile compared with that of one or more reference profiles is to be used to determine the validity of stated biological relatedness among individuals

Page 4: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

• Interpretation of a result:

• 1. Non-match - exclusion

• 2. Inconclusive - no decision

• 3. Match - estimate frequency

Page 5: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

What is an Exclusion?

Single Source: DNA profiles of the evidence and reference samples differ from each other at one or more loci; i.e., barring sample mix-up and/or false identity of samples, reference individual is not the source of DNA found in the evidence sample

DNA Mixture: Reference DNA profile contains alleles (definitely) not observed in the evidence sample for one or more loci; i.e., reference individual is excluded as a part contributor of the mixture DNA of the evidence sample

Kinship: Allele sharing among evidence and reference samples disagrees with the Mendelian rules of transmission of alleles with the stated relationship being tested

Page 6: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

What is an Inclusion?

Single Source: DNA profiles of the evidence and reference samples are identical at each interpretable locus (also called DNA Match); i.e., reference individual may be the source of DNA in the evidence sample

DNA Mixture: Alleles found in the reference sample are all present in the mixture; i.e., reference individual can not be excluded as a part contributor of DNA in the evidence sample

Kinship: Allele sharing among evidence and reference samples is consistent with Mendelian rules of transmission of alleles with the stated relationship being tested; i.e., the stated biological relationship cannot be rejected

Page 7: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

When is the Observation at a Locus Inconclusive?

• Compromised nature of samples tested failed to definitively exclude or include reference individuals

• May occur for one or more loci, while other loci typed may lead to unequivocal definite inclusion/ exclusion conclusions

• Caused often by DNA degradation (resulting in allele drop out), and/or low concentration of DNA (resulting in alleles with low peak height and/or area) for the evidence sample

Page 8: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Quantitative statement that expresses the rarity of the DNA

profile

So, what are we really after?

Page 9: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

• Needed most frequently with an inclusion• (Apparent) exclusionary cases may also be sometimes

subjected to statistical assessment, particularly for kinship determination because of genetic events such as mutation, recombination, etc.

• Loci providing inconclusive results are often excluded from statistical considerations

• Even if one or more loci show inconclusive results, inclusionary observations of the other typed loci can be subjected to statistical assessment

Statistical Assessment of DNA Evidence

Page 10: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

• Exclusion – numbers are not needed

• Match - requires a numerical estimate (weight of

evidence)

Exclusion vs Match

Page 11: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Statistical Analysis

About Evidence sample “Q”

• “K” matches “Q”

• Who else could match “Q“

• Who is in suspect population?

• partial profile, mixtures

Page 12: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Estimate genotype frequency

1. Frequency at each locus

Hardy-Weinberg Equilibrium

2. Frequency across all loci

Linkage Equilibrium (multiply)

Page 13: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Terminology

Genetic marker variant = allele

DNA profile = genotype

Database = table that provides frequency of alleles in a population

Page 14: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Where Do We Get These Numbers?

1 in 1,000,000

1 in 110,000,000

Page 15: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

POPULATION DATAand

Statistics

DNA databases are needed for placing statistical weight on DNA profiles

Page 16: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

RARITYof a profile

PROBABILITYThe most common

13 locus frequency is African Americans1 in 155 billion

Caucasians1 in 188 billion

SW Hispanics 1 in 40 billion

Chinese1 in 59 billion

Apaches1 in 860 million

Page 17: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Human Beings23 different chromosomes

2 sets of chromosomes (from mom and dad) – two copies of each marker

Each genetic marker on different chromosome

Thus, each marker treated like coin toss – two possibilities

Page 18: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Alleles in populations –

The Hardy-Weinberg Theory

Basis: Allele frequencies are inherited in a Mendelian fashion and frequencies of occurrence follow a predictable pattern of probability

Page 19: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

The Hardy-Weinberg principle states: that single-locus genotype frequencies after one generation of random mating can be represented by a binomial (with two alleles) or multinomial (with multiple alleles) function of the alleles frequencies

Page 20: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Hardy - Weinberg Equilibrium

freq(A1) = p1 freq(A2) = p2

Two Allele System

P12 + P2

2 = 12p1p2 +

p1 + p2 = 1

(p1 + p2)2 = 12

A1A2 A2A2A1A1

Page 21: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Approaches for Statistical Assessment of DNA Evidence

Frequentist Approach: indicating the coincidental chance of the event observed

Likelihood Approach: indicating relative support of the event observed under two contrasting (mutually exclusive) stipulations regarding the source of the evidence sample

Bayesian Approach: providing a posterior probability regarding the source, when data in hand is considered with a prior probability of the knowledge of the source (latter is not generally provided by the DNA profiles being considered for statistical assessment)

Page 22: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Frequentist Approach of Statistical Assessment for Transfer Evidence

• When the evidence sample DNA profile matches that of the reference sample, one or more of the following questions are asked:

• How often a random person would provide such a DNA match? Equivalently, what is the expected frequency of the profile observed in the evidence sample? – also called Random Match Probability, complement of which is the Exclusion Probability

• What is the expected frequency of the profile seen in the evidence sample, given that it is observed in another person (namely in the reference sample) – also called Conditional Match Probability

• What would be the expected frequency of the profile seen in the evidence sample in a relative (of specified kinship) of the reference individual, given the DNA match of the reference and evidence samples – also called the Match Probability in Relatives

Page 23: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Random Match Probability– Estimate frequencies of genotype at a locus

– Use product rule

– Correct for departures due to inbreeding (theta/Fst)

– Multiply estimated genotype frequency of each locus assuming

independence among loci (biological basis)

– Correct for sampling (10 fold rule)

Page 24: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

P O P U L A T I O N D A T Aa n d

S t a t i s t i c s

D N A d a t a b a s e s a r e n e e d e d f o r p l a c i n g s t a t i s t i c a l w e i g h t o n D N A p r o f i l e s

Page 25: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Population

Database samples are typically "convenience" samples that have been obtained from blood banks, parentage labs, sometime even Convicted Felon database samples

A major characteristic of these samples is self-declaration regarding "population affinity" … i.e. Caucasian, Asian, Hispanic, African, etc.

Databases may also be defined based on region…country, state, city, etc.

Page 26: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Population database

• Look up how often each allele occurs at the locus in a population (or populations)

• looking up the “allele” frequency

Page 27: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.
Page 28: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.
Page 29: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

13 CODIS Core STR Loci with Chromosomal Positions

CSF1PO

D5S818

D21S11

TH01

TPOX

D13S317

D7S820

D16S539 D18S51

D8S1179

D3S1358

FGA

VWA

AMEL

AMEL

Biological Basis

Page 30: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Profile Frequency Estimates Across Multiple Loci

Employ the PRODUCT RULE

Page 31: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Product Rule

The frequency of a multi-locus STR profile is the product of the genotype frequencies at the individual loci

ƒ locus1 x ƒ locus2 x ƒ locusn = ƒcombined

Page 32: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Overall profile frequency =

Frequency D3S1358 X Frequency vWA

0.0943 x 0.0866 = 0.00817

Page 33: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Random match probability = .000001

Random match probability = 1/1,000,000

Exclusion probability = .999999

Exclusion probability = 99.9999%

Page 34: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

What do these numbers mean?

Random Match Probability

This is the actual probability of seeing profile/genotype in the metapopulation

(Given that the databases provide a reasonable representation of the population)

Page 35: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

13 CODIS loci typically yield extraordinarily small probabilities

0.0000000000000000154or

1 in 60,000,000,000,000,000 persons

Page 36: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

Random match probability is NOT

Chance that someone else is guilty

Chance that someone else left the

bloodstain

Chance of defendant not being guilty

Page 37: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

PART 3

Page 38: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

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

Page 39: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

The 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.

Page 40: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

DNA Typing Results for Evidence

Page 41: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.
Page 42: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

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 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?

Page 43: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

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?

Page 44: Forensic Statistics From the ground up…. Basics Interpretation Hardy-Weinberg equations Random Match Probability Likelihood Ratio Substructure.

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?