Large Scale Simulation for Education in Forensic DNA Science

doi:10.4236/ce.2011.21003

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Creat ive Educati on

2011. Vol. 2, No. 1, 18 -21

Large Scale Simulation for Education in Forensic DNA Science

Jason M . Ki n ser

Department of Bioinformatics and Computational Biology, George Mas on U niversi ty, Fairfax, USA

Email: [email protected]

Received January 12th, 2011; revised February 24th, 2011; accept ed February 28th, 2011.

Forensi c scienc e education is a ra pidly expandi ng field with se veral univers ities a dding degrees i n many

forens ic scienc e discipl ines. Concurrently, with this expansion is a new push for forensic science educa-

tion i n the secondar y schools. This genera tion of st udents is al so very a dept at comp uter genera ted envi-

ronments. The logical progression is therefore to provide students and instructors with a simulated envi-

ronment t o i mmerse st udent s int o forens ic s cienc e invest igat ions. The Island of Ti r Eb ensëa is a de velop-

ing system that generates a large scale population and forensic scenarios and places the students as the

investigators. Students are provided with a scenario and then generate queries to gain information about

the people involved in the case. They can then draw conclusions about the scenario and compare these

conclusions to the know n answer. The simulat ion is availab le to educat ional ins titutions.

Keywords: Web-Based Education, Forensic Science, DNA

Introduction

Forensic science has become a very popular field in educa-

tion within the last few years. One popular explanation is the

advent of television shows such as CSI. Another contributing

factor though is the recent development in the science itself.

Modern forensic science technology has evolved rapidly in the

past decade. Furthermore, the employment future in the field is

bright with a predicted increase of 20% in jobs before 2018

(Bureau of Labor Statistics, 2011; ForensicScience.net, 2011;

Jaroch; 2011). Colleges and universities have responded to this

need as noted by a recent survey which indicates that the US

now has over 70 degree programs in this field (Tebbett, Wielbo,

& Khey, 2007). Likewise, opportunities for secondary school

stud ent s are in creasi ng i n t he t erms of summer ca mps, s peci alt y

programs and school clubs.

This new generation of students is also very adept in using

computerized social environments with the onset of social net-

works and simulation games. Many studies have indicated that

learning experience for secondary school students is enhanced

through the use of virtual environments and simulations (Akpan

& Andre, 2000; Choi & Gennaro, 1987; Geban, Askar & Ozkan,

1992; Lewis, Stern & Linn) with some studies measuring im-

proved performances (Huppert, Lomask & Lazarowitz, 2002;

Mintz 1993; Willing 1988).

In the study of forensic DNA science it is necessary for stu-

dents to understand the statistics of large populations as well as

the inheritance properties of DNA profiles. This type of analy-

sis is well suited for a large scale simulation which is the foun-

dation of a project named Tir Ebensëa. The simulation provides

students with forensic scenarios and several portals through

which their inquiries can reveal more information about the

case. Students then use spreadsheets to reach conclusions of the

scenarios which can be compared to the known answers. The

simulation is available to educational institutions by request to

the au thor.

Simulation Requirements

The study of human identification through DNA profiles re-

quires several components. The two major components are the

statistical analysis of large populations and the understanding of

the DNA profiles including their inheritance properties. Fu r-

thermore, realism in an investigation must includ e several ot her

complicated facto rs. The simulation incorporates many of these

properties to provide realistic scenarios for the students.

DNA Profiles

Currently, a human DNA profile used in court cases may

consist of three components. The first is STR (short tandem

repeats). In the nuclear DNA there are many loci in which a

small DNA pattern repeats multiple times. A forensic profile

identifies alleles by the number of repeats. The nuclear profile

includes contributions from both biological parents and thus for

each locus there are two values. As an example, a person’s

profile for a single locus could be the allele pair [9,11] which

ind icates along on e strand of th e DNA helix th ere are 9 repeats

and along the other is 11 repeats. However, it is not known

which parent donated which value. There is no worldwide

standard yet on the set of loci used. The FBI database, named

CODIS, uses 13 loci. European countries with their smaller

populations often use a fewer number of loci of which some

differ from the US set.

Consider a case of a single locus. The parents are [7,9] and

[9,10]. A child produced from these two parents will receive

one value from each. Therefore a child could be: [7,9], [7,10],

[9,9] or [9,10] with equal probabilities. It is quite possible to

reconstruct (at least partially) a person’s STR profile from the

profiles of their immediate relatives. Given a case where the

mother is [7,8] and two children are [7,10] and [8,11], it is

possible (excluding mutations) to reconstruct the father’s pro-

file to be [10,11]. Even though the father’s DNA may not be

available it is possible to reconstruct (at least in part) the fa-

J. M. KINSER

ther’s profile.

The second type of DNA profile use is mitochondrial DNA

which is a single stranded DNA loop that exists in multiple

copies in the cytoplasm of a cell. The mitochondrial DNA is

inherited en masse from the mother. Statistically, it is treated as

a single entity rather than a set of values such as in the STR

case. The third type of DNA profile is YSTR which is a set of

repeats b ased on th e Y-chromosome. The Y chromosome exists

only in males and is inherited en masse from the father to the

sons. Statistically, it is treated in a manner similar to the mito-

chondrial DNA.

One of the requirements of the simulation is that each person

has a DNA profile with STR, YSTR (males), and mitochondrial

DNA. Furthermore, it necessary that people inherit their pro-

files from their biological parents. There is also a small possi-

bility of some mutations that must be included.

Ethnicity

In real life the distribution of allele sizes (Butler 2005; Mar-

janovic et al., 2005; Dutta et al., 2002; Nei 1973) varies for

each ethnic group. It is possible to provide a probability of a

person’s ethnicity based upon their DNA profile. Therefore, th e

simulation must have a variety of ethnic groups each with their

own distributions.

Scale

Matching DNA profiles does not prove that a DNA sample

comes from a specific person. There are two conclusions that

can be drawn from an analysis. The first is an exclusion where

it is possible to state that a DNA sample does not come from a

specific person. The second is a probability in which the re-

searcher provides a probability of a random person having a

particular profile. In some cases, this value can be so ridicu-

lously low that it would take several times the Earth’s popula-

tion before there is a significant chance of a second person

having the same profile. While it is not possible to conclude

that a DNA sample comes from a specific person it is possible

to compute that the probability of two people having the same

profile is astronomical.

Before a student can make a statistical calculation from a

sample population it is necessary to gather a subsample popula-

tion. Even though the US population is over 300,000,000

people studies indicate that less than two hundred people are

need to provide a statistically relevant sampling of the popula-

tion (Chakraborty, 1992). In order to replicate this, the si mula-

tion is required to have a large population but not nearly on the

same scale as t he US pop ulation.

In order to replicate this type of analysis it is necessary for

the simulation to have a population base with different ethnic

groups with signature distributions. Furthermore, it is necessary

that t he size of the population be large.

Bi ological versus Le gal Parentage

The DNA profiles are inherited from biological parents.

However, many children live with adults that are legally their

parents but not biologically their parents. This occurs through

re-marriages, adoptions, or infidelities. In some cases, the in-

vestigator may know that the parents are not biologically re-

lated and in other cases this information is not volunteered by

the family members.

Therefore, the simulation must include mechanisms by which

families may be created through means other than biological

evolution. It must include marriages, divorces, re-marriages,

adoptions, and the occasional tryst.

Scenarios

Another major component of a simulation is the creation of

scenarios that are to be solved. In this manner, the students act

as the in vestigators. Scen arios solved by DNA anal ysis inclu de

missing persons, assaults, thefts, scams, law suits, and mass

disaster s. Each scenario presents stu dents with a s mall descrip-

tion and then they interact with the simulation to retrieve other

information that is necessary. A sample case is presented in a

subsequent section.

Require me nts

A simulation of forensic DNA cases must include a large

population with ethnic variations. This population must have

biological relationships in order to replicate inheritance, but it

also must h ave mechanis ms by which these biological rel ation-

ships are disconnected. The simulation must also create scena-

rios suitable for students educational and maturit y levels.

The Tir Ebensëa Simulation

With the requirements in hand the simulation named The

Island of Tir Ebensëa has been created and is available to edu-

cational institutions. The simulation provides a large scale pop-

ulation, portals for inquiry, and forensic scenarios with solu-

tions.

The Island of Ti r Eben sëa

The simulation is based upon a theoretical island inhabited

by four ethnic groups. The population occupies five cities as

well as the coun try-side. Since DNA profile statistics are shown

to be sensitive to regions and ethnic groups, four of the five

cities contain a majority of one of the ethnic groups. This al-

lows students to study profile distributions for global, local,

ethnic and/or chronological populations.

The population is evolving at a rate of 10 years per school

semester. Simulants (people in the simulation) age, die, marry,

give birth , etc. du rin g th e cour se of a semester. A recen t sa mple

from the i sland from year 16 27 indicates t hat there have been a

total of 118,000 people of which 24,122 are currently living.

There are four ethnic groups which do marry across racial

boun daries at small rates and there are curr ently 1759 d ifferent

surnames. Figu re 1 shows the distribution of ages of the current

living population. There are two spikes for the younger ages

due to two recent immigration influxes.

The Si mulant s

Each simulant in the population contains a personality which

includes the propensity to commit speci fic criminal act s. Figure

2 displays the distribution of one of the personality factors

which controls the willingness of an individual to cooperate

with the police. Two spikes at the end of the distribution indi-

cate that there are several p eople that will always or never co o-

perate. There is a nontrivial portion of the population that may

cooperate. Students requesting a DNA sample from an individ-

J. M. KINSER

Figure 1.

Dist r ibution of th e ages of the living population.

ual may be denied this information because the simulant does

not cooperate, but the students will not know if this is a tempo-

rary blockade, and requests on different days may produce a

different result.

Figur e 2 depicts on a log y scale the propensity for individuals

in the population to commit a specific criminal act (crime type

1). In this sample, more than 10,000 people have absolutely no

tendency to commit this act. A few hundred people (to the right

of x = 90) are quite capable of committing this act. Several other

personality and criminal propensities are used to describe the

personality of each simulant and some of these qualities are

partially inh erited. Fi gure 3 display s the distribution amongst the

pop u l at i on of a sp e ci fic cri mi n a l te nden cy wher e a la r ger x value

indicates a higher pr o pensi ty to commit this type of cr ime. Cases

are developed bas ed on a person’s criminal tendency profile thus

creating individuals that are recidivists.

Student Interface

Students are required to have two computer tools in order to

participate. The first is access to a web browser to interface

with the simulation and the second is a spreadsheet. The web

sites provide portals in which the students can submit queries.

The results are returned as grids which they copy into their

spreadsheets. Example sheets are available to demonstrate the

methods in which a spreadsheet can be used to complete the

computation. Currently, the material that the student turns in to

the instructor is a small report and the spreadsheet.

Initially, students request a population sampling which they

use to create their base profile distributions. A tool is provided

to create these tables from raw data. Students store this infor-

mation in a spread sheet which wil l be used in almost all scena-

rios. This process is performed just once. When students re-

ceive a scenario they create a new spreadsheet file and store

results from their queries. They also create a copy of th e sheets

from the population sample and add a few cells to compute the

probabilities.

While these steps could be automated, the spreadsheet me-

thod provides a better teaching too l. Stu dents can s ee the stat is-

tics and how they are created and combined to provide a solu-

tion. S tudents need to have a basic knowledge o f statistics ( av-

erages and standard deviations) as well as an introduction to a

Figure 2.

Distribution of cooperation factors.

Figure 3.

Distri butio n or propensi ties to comm it crim e ty pe 1.

few tools used in the forensic industry (Hardy-Weinberg and

upper bounds). These formulae are well within the educational

level of scien ce-minded middle school students.

Students formulate their conclusions which may include ex-

clusions or probabilities. Then the actual solution to the scena-

rio is made available through their instructor. One of the ad-

vantages of using simulation data over real world cases is that

the solution is definitely known.

Finally, tracking software has been installed to follow the

line of inquiry by each student. Information that is easily ob-

tained from this includes the number of queries and the simu-

lants that are being investigated by the students. A simple ar-

gument is that students that achieve results with a minimal

number of queries have performed a better investigation than

students that generate unnecessary queries. However, there are

complicating factors that come with an evolving population.

For example, queries performed on different days may provide

different results since some of the simulants may have died or

been p laced in the j ail. So, the number of inquiries is deemed to

be important but not the only metric.

J. M. KINSER

Sample Case

This section presents a case recently used that indicates the

type of logic that students will need in order to solve a scenario .

In this case, the victim was a discovered body in the forest.

Evidence provided to the students was that the victim was an

adult male, the ethnic group was identified, and the DNA pro-

file of the victim was identified.

The following steps were the ones necessary for the proper

solution.

1) Request a list of missing persons from the Missing Per-

sons Bureau. Exclude from consideration all those that were not

adul t males.

2) Prioritize the remaining persons according to location and

ethnicity.

3) For each person on the list, contact their immediate fami-

lies and request DNA samples.

4) Exclude from the candidate list those whose DNA profiles

had several mismatches with the victim.

In th is case, only one male (Stanton Updegraff) survived the

previous pruning steps. The following steps were used to con-

firm the identity of the victim.

5) Determine that there were inconsistencies with the DNA

of the wife (Kesha) and three children. From this analysis the

students conclude that Kesha is not the biological mother of the

children.

6) Through queries to other agencies students gather birth

records and marriage records. From this they learn that Stanton

was previously married to Serena and that the birth of the three

children was during this first marriage.

7) Use Seren a and the thr ee children to reconstru ct Stanton’s

DNA profile. In the initial analysis there are some inconsisten-

cies in the reconstruction and the reconstructed profile does not

match the victim. The early conclusion is that the victim is not

Stanton. However,…

8) Th e inconsistenci es trigger students to realize that one (or

more) of the children has a different biological father. Using

Y-chromosome information students conclude that the two sons

have the sa me bio logical father and that th e Y data matches the

victim. Therefore, they consider a reconstruction without the

daughter.

9) The new reconstruction shows no mismatches between

Stanton and the victim.

10) Students then use statistical tools to compute the proba-

bility that a random person could have Stanton’s reconstructed

profile. This leads them to conclude that there is an extremely

high probability that the victim is Stanton. This is the correct

answer.

This case requires the students to use several tools. Students

will need to be able to reconstruct DNA profiles from relatives,

use Hardy-Weinberg statistics to compute probabilities, and

most importantly to understand the evidence. Twice in this case

students would have to understand that the evidence indicates

that oth er peop le are invo lved in the case ( first wi fe and ano th er

male partner). These latter two conclusions are not derived

from computer tools but solely from the student’s ability to

understand the evidence before t hem.

Final Comments

The current version of the simulation is Tir3 with two new

versions in the pipeline that will add other types of forensic

evidence (other than DNA) and new environments. Instructors

may access the simulation through a request through to the

author. Access is currently controlled but not highly restrictive.

Instructors wishing to participate in this project should contact

the author. Sample cases of the simulation are found on the

accompanying web site: http://binf.gmu.edu/kinser/fdna09/

tirsimulation/.

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