State v. Simmer , 304 Neb. 369 ( 2019 )

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Nebraska Supreme Court Advance Sheets
304 Nebraska Reports
STATE v. SIMMER
Cite as 304 Neb. 369
State of Nebraska, appellee, v.
Charles M. Simmer, appellant.
___ N.W.2d ___
Filed November 1, 2019. No. S-18-500.
1. Expert Witnesses: Appeal and Error. The standard for reviewing the
admissibility of expert testimony is abuse of discretion.
2. Judgments: Expert Witnesses: Words and Phrases. An abuse of dis-
cretion in the trial court’s determination under Daubert v. Merrell Dow
Pharmaceuticals, Inc., 509 U.S. 579, 113 S. Ct. 2786, 125 L. Ed. 2d 469
(1993), and Schafersman v. Agland Coop, 262 Neb. 215, 631 N.W.2d
862 (2001), occurs when a trial court’s decision is based upon reasons
that are untenable or unreasonable or if its action is clearly against jus-
tice or conscience, reason, and evidence.
3. Courts: Expert Witnesses. Under the Daubert v. Merrell Dow
Pharmaceuticals, Inc., 509 U.S. 579, 113 S. Ct. 2786, 125 L. Ed. 2d 469
(1993), and Schafersman v. Agland Coop, 262 Neb. 215, 631 N.W.2d
862 (2001), framework, the trial court acts as a gatekeeper to ensure the
evidentiary relevance and reliability of an expert’s opinion.
4. Trial: Expert Witnesses: Intent. The purpose of the gatekeeping
function is to ensure that the courtroom door remains closed to “junk
science” that might unduly influence the jury, while admitting reliable
expert testimony that will assist the trier of fact.
5. Trial: Expert Witnesses. A trial court can consider several nonexclu-
sive factors in determining the reliability of an expert’s opinion: (1)
whether a theory or technique can be (and has been) tested; (2) whether
it has been subjected to peer review and publication; (3) whether, in
respect to a particular technique, there is a high known or potential
rate of error; (4) whether there are standards controlling the technique’s
operation; and (5) whether the theory or technique enjoys general
accept­ance within a relevant scientific community.
6. ____: ____. Once the reasoning or methodology of an expert opinion
has been found to be reliable, the court must determine whether the
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expert’s reasoning or methodology can be properly applied to the facts
in issue.
Appeal from the District Court for Douglas County: Thomas
A. Otepka, Judge. Affirmed.
Thomas C. Riley, Douglas County Public Defender, for
appellant.
Douglas J. Peterson, Attorney General, and Melissa R.
Vincent for appellee.
Heavican, C.J., Miller-Lerman, Cassel, Stacy, Funke,
Papik, and Freudenberg, JJ.
Papik, J.
Charles M. Simmer appeals his conviction for first degree
murder. DNA evidence presented at Simmer’s jury trial linked
him to the crime. The sole issue presented by this appeal is
whether the district court erred in admitting DNA analysis con-
ducted by using TrueAllele probabilistic genotyping software,
over Simmer’s Daubert/Schafersman challenges. Finding no
abuse of discretion, we affirm.
I. BACKGROUND
1. Overview
On November 3, 2007, Simmer’s aunt, Joy Blanchard, was
murdered in her home. She was discovered lying face down on
the floor with two knives protruding from her neck. Close by
was a spindle broken from the nearby bannister. An autopsy
revealed the cause of death to be blunt force trauma and stab
wounds to the head and neck.
When law enforcement processed the crime scene, they
swabbed several items for DNA, including the spindle, the
handles on both knives, and the interior doorknob on the front
door of the residence. DNA testing and analysis conducted in
2015 and 2016 indicated the presence of Simmer’s DNA on
one of the knife handles and the interior doorknob.
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STATE v. SIMMER
Cite as 304 Neb. 369
On June 7, 2016, Simmer was charged by information
in Douglas County District Court with one count of first
degree murder, a Class IA felony. Prior to trial, Simmer filed
a motion in limine asserting a challenge to DNA analysis
performed by Cybergenetics, Inc., which challenge was pur-
suant to Daubert v. Merrell Dow Pharmaceuticals, Inc., 509
U.S. 579, 113 S. Ct. 2786, 125 L. Ed. 2d 469 (1993), and
Schafersman v. Agland Coop, 262 Neb. 215, 631 N.W.2d 862
(2001) (Daubert/Schafersman). He sought to preclude the
State from introducing at trial “any and all testimony concern-
ing DNA testing and the results of said testing,” including
“identification” and “comparison” of DNA testing. Simmer
alleged that the reliability of the theories, techniques, and pro-
cedures used by the State’s experts had not been established
and that the proposed testimony was “based on insufficient
facts and data.” Hearings were held on the motion, and the
district court overruled it.
At the subsequent jury trial, Simmer preserved the Daubert/
Schafersman challenges raised in his pretrial motion. He
lodged a continuing objection when Dr. Mark Perlin, the chief
scientist and executive officer at Cybergenetics, was called
to testify about TrueAllele probabilistic genotyping and its
application in this case. The district court overruled the objec-
tion. The jury heard DNA evidence and other circumstan-
tial evidence connecting Simmer to Blanchard’s murder, and
Simmer was convicted of the crime charged and sentenced to
life imprisonment.
The sections below summarize the Daubert/Schafersman
proceedings and the relevant evidence at trial.
2. Daubert/Schafersman Proceedings
At pretrial proceedings on Simmer’s motion in limine, the
district court received exhibits and heard expert testimony
about DNA evidence from three witnesses. Generally, Mellissa
Helligso’s testimony provided context for Perlin’s testimony
about Cybergenetics’ TrueAllele probabilistic genotyping
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program. Simmer elicited testimony from Nathaniel Adams to
challenge TrueAllele’s methodology.
(a) Testimony of Helligso
Helligso, a forensic DNA analyst employed by the University
of Nebraska Medical Center (UNMC), testified about the DNA
tests that she performed in this case. Helligso explained the
process by which an autosomal DNA profile is obtained and
analyzed. Upon receiving evidence containing biological mate-
rial, she extracts the DNA, quantifies and amplifies it, and ulti-
mately runs it through a genetic analyzer. The genetic analyzer
generates a DNA profile that can then be compared to DNA
from known individuals. Typically, the analysis is limited to
specific locations in the DNA and does not include a full pro-
file. If she identifies consistencies between the evidence profile
and the known individual’s profile, she will “generate a statis-
tic to show the likelihood of that match happening.”
Helligso also explained the difference between autosomal
DNA and Y-STR DNA. Humans have 23 pairs of chromosomes
with each pair consisting of one each from the father and
mother. The term “allele” describes the varying forms of a gene
that can be specific to an individual but found for everyone at
the same place in the same chromosome. Differences in alleles
at predetermined chromosome locations, referred to as “loci,”
define a person’s DNA profile and can be used for comparison
with evidence samples.
Helligso explained that autosomal DNA is composed of
DNA inherited from both parents. Y-STR DNA, on the other
hand, involves only the Y chromosome, which is found only in
males and is passed from father to son. Because all males in
the same family have the same Y-STR DNA, it cannot identify
a particular male within that family and is less discriminating
than autosomal DNA. In Y-STR DNA testing, a DNA extract is
amplified with a particular “kit” that only looks at the Y-STR
locations found on the Y chromosome.
In this case, among the items that Helligso received in
2007 were swabs obtained from one of the knife handles and
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the spindle. Y-STR DNA testing of both items disclosed the
presence of two Y chromosomes, indicating a mixture of two
males. Simmer could not be excluded as the major male con-
tributor in either sample, but neither could his brother, since
they share the same Y chromosome. The probability of a match
was stronger on the knife handle than on the spindle.
In November 2015, Helligso received several additional
items for testing, including a swab from the interior doorknob
on the front door to Blanchard’s residence. Helligso deter-
mined the sample contained autosomal DNA from at least two
individuals. Neither Blanchard nor Simmer could be excluded
as full contributors on the doorknob, and “[t]he probability of
a random individual matching a DNA profile within the mix-
ture, given that . . . Simmer expresses such a profile, [was] 1
in 357 million . . . for Caucasians, 1 in 844 million . . . for
African Americans, and 1 in 2.37 billion . . . for American
Hispanics.”
Helligso suggested sending her work to Perlin at
Cybergenetics for additional analysis. To provide the back-
ground for that decision, Helligso explained the process by
which a DNA profile is obtained and analyzed and the sig-
nificance of data “thresholds.” She stated that for any type
of testing done by UNMC, the laboratory must go through a
validation process:
[O]ne of the things that you have to establish is your
threshold, which is the height at which, in your labora-
tory, you can determine the difference between what
would be considered a real peak or real allele and back-
ground noise of the instrumentation, because every instru-
ment has background noise just by the technology in
which it works. And so every laboratory, for their own
instrumentation, has to determine where that cutoff lies
within the data.
....
. . . In our laboratory, the threshold for autosomal, and
I believe for Y-STR in this case as well, was set at 50
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[relative fluorescence units (RFU)]. So any peak that is
below 50 RFU does not get labeled by the software pro-
gram that we have, so then we, in general, do not look at
those peaks. They can be considered if you’re trying to
determine if you have a mixture, but, in general, no, we
don’t look at those peaks then.
Helligso explained that at UNMC, none of the data below the
threshold is used in her statistical calculations.
Helligso testified that Cybergenetics had developed a soft-
ware program that is not bound by data thresholds. Using
a series of mathematical calculations, the software analyzes
every peak to determine whether it is “an artifact [or] a real
allele.” Helligso also testified that Perlin does not retest the
evidence; rather, his software simply uses all the data compiled
by the laboratory during its analysis. Helligso testified that
the human brain could perform the same calculations as the
software, but it would require “an extreme amount of time.”
She stated that it makes sense to use software that performs the
necessary calculations quickly and accurately.
Helligso testified that probabilistic genotyping has “defi-
nitely been a hot topic for a couple of years now.” When
Helligso was asked whether there was some dispute about
the general acceptance of Perlin’s approach in the broader
scientific community, Helligso replied, “[I]f you [had] asked
me that question six or seven years ago, I would have agreed,
but I would say now within the last five years that, in gen-
eral, the community is — is agreeing that these types of
software programs are necessary.” The number of people who
do not agree are “becoming fewer and fewer.” She pointed
out that TrueAllele addresses a need in the DNA analysis
community by facilitating the use of all of the DNA data
to calculate a “good statistic.” Helligso noted that the accu-
racy of TrueAllele software had been tested over at least 10
years with thousands of known profiles with an “extremely
high success rate.” She also noted that a similar program,
“STRmix,” is “being highly touted by the FBI and the
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national government” and “has kind of taken off to where lots
of laboratories have those.”
(b) Testimony of Perlin
As noted above, Perlin is the chief scientist and executive
officer at Cybergenetics, a bioinformation company. He testi-
fied about his company’s software, TrueAllele, and its applica-
tion in Simmer’s case.
Perlin explained that TrueAllele is designed to separate the
various contributors to DNA samples processed by crime labo-
ratories and assess the likelihood that a contributor matches a
known sample. Like Helligso, Perlin testified that TrueAllele’s
method of analysis differs from traditional DNA analysis per-
formed by humans in that TrueAllele does not utilize thresh-
olds, which exclude or discard data that falls below a prede-
termined level. Instead, it analyzes all of the data, taking into
account peak heights and other patterns. According to Perlin,
TrueAllele yields more accurate results, that is, it can produce
a stronger “match statistic” or, alternatively, exclude an indi-
vidual who may have otherwise been included.
Crime scene samples can consist of very small amounts of
DNA, incomplete DNA, and DNA from more than one con-
tributor. Using a series of complex probability equations and
statistical sampling, TrueAllele tries out thousands of possible
explanations, or possible genotypes, for the crime scene data,
and calculates the probability of each explanation. Those that
explain the data well generate higher probability, while those
that explain the data not as well, or not at all, generate lower
probability. This process suggests genotypes and their prob-
abilities at every genetic location for each contributor to the
crime scene sample.
Perlin testified that TrueAllele ultimately infers a genotype,
or DNA barcode, for each contributor to the crime scene evi-
dence, which is a probability distribution over possible allele
pairs, and then calculates the probability that an inferred
genotype matches (1) the suspect and (2) a random person in
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the population. The program then divides the former by the
latter to generate a likelihood ratio or “match statistic.” The
match statistic answers the question: “How much more does
the suspect match the evidence at this location than a ran-
dom person?”
Perlin explained that TrueAllele is more objective than the
traditional method, because the computer analyzes the data
without comparing it to a known sample from a suspect or
“anybody’s preferred answer.” A suspect’s genotype is not
given to the computer until it calculates the match statistic.
Perlin recounted the development of TrueAllele. Perlin, who
has a bachelor’s degree in chemistry, is a doctor of medicine,
and has Ph.D.’s in mathematics and computer science, began
using computers to interpret genetic information in the early
1990’s while working on the Human Genome Project. At that
time, he became involved in the development of software
that would enable a computer to understand and eliminate
artifacts in DNA data. He continued that work after founding
Cybergenetics in 1994 and published his first article on the
subject in 1995. Over the course of 15 years, Perlin devel-
oped TrueAllele. TrueAllele is based on “Bayesian” prob-
ability modeling and “Markov chain Monte Carlo” statistical
sampling, both widely accepted in the relevant communities
for decades. Perlin testified that TrueAllele uses mathemat-
ics and algorithms developed 20 years prior to trial, with the
“core math of calculating genotypes [remaining] the same
since 2008.”
Perlin testified that TrueAllele is widely used. He stated
that he and his company have been extensively involved in
educating and training laboratory analysts to use TrueAllele.
Perlin testified that at least 10 laboratories around the coun-
try have used TrueAllele, 7 of them regularly, and have done
their own internal validations of the software. TrueAllele had
conducted analyses in at least 500 cases in 37 states, though
not all of the analyses were used in court. Further, TrueAllele
had been used to analyze small quantities of damaged DNA
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from thousands of human remains to help identify victims of
the September 11, 2001, terrorist attack on the World Trade
Center. Perlin also testified that TrueAllele had been used
by the DNA group at the National Institute of Standards and
Technology, a part of the U.S. Department of Commerce that
“create[s] resources for the forensic community in the U.S.
and the world that are standards.” He stated that the national
institute had used TrueAllele to create standards for a DNA
mixture against which laboratories could check their equip-
ment and methods.
Perlin testified that TrueAllele had been used in court pro-
ceedings. He stated that he had testified in at least 10 admissi-
bility hearings and that no court had found his testimony to be
inadmissible. The district court received nine trial court admis-
sibility rulings from other jurisdictions in the United States
allowing TrueAllele evidence, five of them applying a Daubert
standard. Perlin testified that Cybergenetics does work for
both the prosecution and the defense. He noted that TrueAllele
had been used in more than 10 cases by the Innocence Project,
a group that seeks to exonerate the wrongly convicted. Perlin
testified that Cybergenetics screens DNA from any group at no
cost and only charges for additional services, such as a written
report or testimony. He also stated that TrueAllele provides
the opportunity for any group to run its software for free to
independently confirm results and that results could also be
confirmed through competing software.
Perlin also testified concerning approval of TrueAllele by
the Scientific Working Group on DNA Analysis Methods
(SWGDAM). SWGDAM is composed of highly respected
individuals in the DNA analysis community who author guide-
lines for DNA analysis that are often adopted by accrediting
agencies. SWGDAM approved the use of probabilistic geno-
typing software in 2010, as long as it had been validated and
documented. And in 2015, SWGDAM issued guidelines for
validating probabilistic genotyping programs, centering on lab-
oratory validation, sensitivity, specificity, and reproducibility.
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Sensitivity reflects the extent to which interpretation identi-
fies the correct person, specificity reflects the extent to which
interpretation does not identify the wrong person, and repro-
ducibility reflects the extent to which interpretation consist­
ently gives the same answer to the same question. According
to Perlin’s testimony and documentary evidence generated by
Cybergenetics, TrueAllele complies with those guidelines.
The district court received numerous validation studies of
TrueAllele. Perlin described validation studies as “tests that
are done where known data is put into a method, like a com-
puter program for calculating match statistics, and the results
are assessed on 10 to 100 samples, depending on the study,
and its performance is measured, along with error rates.”
According to Perlin, 34 studies conducted by the TrueAllele
laboratory and other crime laboratories and groups had shown
that TrueAllele produces accurate and reliable results with
“no surprises.”
Perlin stated that typically in the field of science, a method
like TrueAllele would be featured in only one peer-reviewed
publication. However, of the 34 validation studies in evi-
dence, 7 studies had been published in peer-reviewed jour-
nals and 6 of the 7 studies in evidence identified Perlin as a
coauthor.
Perlin testified that TrueAllele’s error rates had been tested
multiple times in two ways, which Perlin described in detail.
First, error rates had been tested through validation studies of
large ensembles of “real,” “less pristine” samples from case-
work to demonstrate how the system works in practice. And
second, error rates were tested by the application of informa-
tion theory to determine the expected distribution of match
statistics from one evidence genotype of known composition
to “provide information about a sample in a case and what
the error rate would be for a particular match statistic.” Of the
seven peer-reviewed validation studies, four used laboratory
samples of known composition and three drew from less pris-
tine crime scene data.
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In this case, Perlin used TrueAllele to analyze the data
from UNMC and calculated likelihood ratios for Simmer on
both the knife handle and the doorknob. According to Perlin’s
analysis, the match between the knife handle and Simmer was
3.71 thousand times more probable than a coincidental match
to an unrelated person, while the match between the doorknob
and Simmer was 4.22 quintillion times more probable than a
coincidental match to an unrelated person. Perlin also calcu-
lated likelihood ratios for Simmer’s brother as to both items;
however, his ratios were exclusionary.
Other portions of Perlin’s testimony are mentioned, as rel-
evant, in the analysis section below.
(c) Testimony of Adams
Adams has a bachelor’s degree in computer science and is
employed by a company that “consult[s] with lawyers to help
them understand what kind of [DNA] testing was conducted,
whether there are any issues with that testing with the analysis
or interpretation of the data.” The company reviews “standard
operating procedures, validation studies of the testing labo-
ratories, [and] relevant literature in the forensic DNA field.”
Adams’ duties involve the review of electronic data generated
during the course of forensic DNA testing and case files from
criminal investigations involving DNA testing.
Adams’ testimony and written report expressed concerns
about the validity of TrueAllele’s probabilistic genotyping pro-
gram from a software engineering perspective. Adams’ primary
objection to the software was that it had not been confirmed
that the software does what Perlin says it does. He testified,
“This is one of the major topics of verification and validation
. . . in the field of software engineering. We need to demon-
strate, not just assume or expect, that a program is operating as
described . . . .”
Adams testified that the problem with probabilistic geno-
typing programs like TrueAllele is that “[t]he field of forensic
DNA does not have any standards specific to it that software
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must adhere to before it’s utilized in casework.” He stated
that TrueAllele encompassed computing statistics and biology
and that minimum quality assurance standards required a mul-
tidisciplinary, multiparty approach. Adams’ report acknowl-
edged that the International Society of Forensic Genetics
and SWGDAM had published guidance documents addressing
validation of probabilistic genotyping software, but the field
of forensic DNA analysis still lacked formal standards spe-
cific to its development and validation. His report observed
that while there were no common software development stan-
dards for probabilistic genotyping, general software engineer-
ing industry standards and principles could be used to ensure
correctness of the systems. However, this had not been done.
As a result, he contended that defects may exist in the soft-
ware and that their significance to its operation would per-
sist undetected.
Adams noted that a program’s source code, the program-
ming language instructing the computer what to do, can be
inspected to determine whether the software program has been
appropriately constructed. However, according to Adams, the
TrueAllele source code had never been independently reviewed
to determine whether the program operates as described by
Perlin. The district court received evidence that Cybergenetics
had recently decided to allow defense experts access to the
TrueAllele source code, with limitations. In Adams’ view,
reviewing the source code in the context of a particular case
was prohibitive under the time and financial constraints of
litigation, especially if certain software development materials
were not involved in the review. In Adams’ opinion, review of
the source code ought to occur over a long period prior to use
in a criminal case.
Adams acknowledged that one way to determine whether
a program works as intended is to use it, but that it was not
the only way under software engineering general practices for
quality assurance. He considered it “dangerous to allocate our
only software defect detection efforts to the actual use of that
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software” because of the significant impact latent defects could
have. Adams testified that TrueAllele had achieved only the
“illusion of validation” because it had not been validated in the
domain of software engineering. And while he also acknowl-
edged that TrueAllele had been developed over a period of sev-
eral years before it was ever used in a criminal case, he stated
that he still had concerns about it since he “[didn’t] know what
defect prevention or mitigation strategies were employed dur-
ing that time.”
In addition, Adams’ report questioned validation studies of
the quantitative likelihood ratios generated by probabilistic
genotyping “because no knowable correct output exists for
any given input, against which the system’s behaviors could
be tested.” Adams explained that “we can’t know exactly what
likelihood ratio should be developed, even if we know the
inputs to the systems, the genotypes of the true contributors.”
Adams also expressed concern about the accuracy of like-
lihood ratios in general, even with known contributors, and
stated that while he also has concerns about the accuracy of
traditional DNA analysis, he prefers it to computer programs
because it is more transparent and its calculations “can be
replicated by anybody with a pocket calculator or an Excel
spreadsheet.”
(d) Motion in Limine Overruled
Following the hearing, the district court overruled Simmer’s
motion in limine. It found Perlin to be an expert in the field
of probabilistic genotyping. The district court further found
that the TrueAllele evidence was relevant and that it would
be helpful to the finder of fact in this case. The district court
applied the Daubert/Schafersman analytical framework and
determined the methodology of TrueAllele probabilistic geno-
typing was reliable, noting that the Daubert test was flexible
and that not every factor need be considered. We summa-
rize the district court’s ruling in detail in the analysis sec-
tion below.
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3. Relevant Evidence at Trial
At trial, the State presented DNA evidence connecting
Simmer to the crime scene. Helligso and Perlin both gave
testimony consistent with their testimony at the hearing on
Simmer’s motion in limine. Helligso testified that her analy-
sis showed that neither Simmer nor his brother could be
excluded as the major male contributor to DNA on the spindle
and the knife handle. As for the DNA on the interior door-
knob, Helligso’s analysis determined that the sample con-
tained a mixture of at least two individuals and that neither
Blanchard nor Simmer could be excluded as full contribu-
tors. She stated that the probability of a random individual
matching a DNA profile within the mixture on the inte-
rior doorknob, given that Simmer expresses such a profile,
was 1 in 357 million. Regarding the TrueAllele analysis
of the evidence in this case, Perlin testified that the match
between the knife handle and Simmer was 3.71 thousand
times more probable than a coincidental match to an unrelated
person, while the match between the doorknob and Simmer
was 4.22 quintillion times more probable than a coincidental
match to an unrelated person. As he did at the hearing on
Simmer’s motion in limine, Perlin also described at trial how
TrueAllele works.
In addition to DNA evidence, the State introduced other evi-
dence linking Simmer to Blanchard’s murder. Although there
was no direct evidence that Simmer had been at Blanchard’s
residence on the night of the murder, from early on, he was
a suspect in the police investigation. The State presented
evidence at trial that Simmer had not been to Blanchard’s
residence during the 21⁄2 years prior to Blanchard’s murder;
that Simmer had misinformed police about his whereabouts
during the timeframe of Blanchard’s murder; that 2 days after
the murder, Simmer tried to conceal injuries to his hands from
police; that he physically resisted providing a court-ordered
DNA sample; and that about 3 months after the murder, he had
confided in a friend about stabbing someone to death.
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II. ASSIGNMENTS OF ERROR
Simmer assigns that the district court committed reversible
error in rejecting his Daubert/Schafersman challenge and in
allowing the State to present Perlin’s expert opinion testimony
and evidence concerning Perlin’s conclusions on DNA evi-
dence connecting Simmer to the crime scene.
III. STANDARD OF REVIEW
[1,2] The standard for reviewing the admissibility of expert
testimony is abuse of discretion. State v. Tucker, 301 Neb. 856,
920 N.W.2d 680 (2018). An abuse of discretion in the trial
court’s Daubert/Schafersman determination occurs when a trial
court’s decision is based upon reasons that are untenable or
unreasonable or if its action is clearly against justice or con-
science, reason, and evidence. State v. Hill, 288 Neb. 767, 851
N.W.2d 670 (2014).
IV. ANALYSIS
Simmer’s sole assignment of error challenges the admission
of TrueAllele probabilistic genotyping evidence linking him to
the crime scene. While Simmer’s appeal focuses exclusively
on the admission of this evidence, his arguments fall into two
different categories within the Daubert/Schafersman analysis.
Simmer makes a number of arguments aimed at the general
reliability of TrueAllele. Other arguments focus on whether
TrueAllele, even if generally reliable, was properly applied to
the facts in this case. After briefly reviewing the basic govern-
ing legal principles, we will proceed to analyze Simmer’s argu-
ments in turn.
1. Daubert/Schafersman Standards
The Nebraska Evidence Rules provide: “If scientific, tech-
nical, or other specialized knowledge will assist the trier of
fact to understand the evidence or to determine a fact in issue,
a witness qualified as an expert by knowledge, skill, experi-
ence, training, or education, may testify thereto in the form
of an opinion or otherwise.” Neb. Evid. R. 702, Neb. Rev.
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Stat. § 27-702 (Reissue 2016). Perlin’s qualifications are not
at issue in this appeal. Rather, Simmer argues that the State
failed to demonstrate that the TrueAllele evidence was admis-
sible under the Daubert/Schafersman framework and that the
district court therefore abused its discretion in allowing it in
evidence. See State v. Casillas, 279 Neb. 820, 782 N.W.2d 882
(2010) (burden is on proponent of evidence to establish admis-
sibility under Daubert/Schafersman).
[3,4] Under the Daubert/Schafersman framework, the trial
court acts as a gatekeeper to ensure the evidentiary relevance
and reliability of an expert’s opinion. Hemsley v. Langdon, 299
Neb. 464, 909 N.W.2d 59 (2018). The purpose of this gate-
keeping function is to ensure that the courtroom door remains
closed to “junk science” that might unduly influence the jury,
while admitting reliable expert testimony that will assist the
trier of fact. State v. Herrera, 289 Neb. 575, 856 N.W.2d
310 (2014). The Daubert/Schafersman standards require proof
of the scientific validity of principles and methodology uti-
lized by an expert in arriving at an opinion. See Hemsley v.
Langdon, supra.
[5] A trial court can consider several nonexclusive fac-
tors in determining the reliability of an expert’s opinion: (1)
whether a theory or technique can be (and has been) tested; (2)
whether it has been subjected to peer review and publication;
(3) whether, in respect to a particular technique, there is a high
known or potential rate of error; (4) whether there are stan-
dards controlling the technique’s operation; and (5) whether
the theory or technique enjoys general acceptance within a
relevant scientific community. State v. Braesch, 292 Neb.
930, 874 N.W.2d 874 (2016). A trial court may consider one
or more of these factors when doing so will help determine
that testimony’s reliability, but the test of reliability is “‘flex-
ible’” and the list of specific factors neither necessarily nor
exclusively applies to all experts or in every case. See Kumho
Tire Co. v. Carmichael, 526 U.S. 137, 141, 119 S. Ct. 1167,
143 L. Ed. 2d 238 (1999), quoting Daubert v. Merrell Dow
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Pharmaceuticals, Inc., 509 U.S. 579, 113 S. Ct. 2786, 125 L.
Ed. 2d 469 (1993).
[6] Once the reasoning or methodology of an expert opinion
has been found to be reliable, the trial court must determine
whether the expert’s reasoning or methodology can be properly
applied to the facts in issue. See State v. Edwards, 278 Neb.
55, 767 N.W.2d 784 (2009).
2. General Reliability of
TrueAllele Evidence
Simmer contends that the State failed to show the evi-
dence generated by TrueAllele was sufficiently reliable under
the Daubert/Schafersman framework. The district court con-
cluded otherwise. In its order denying Simmer’s motion in
limine, the district court first observed that TrueAllele had
been tested by 34 validation studies and that it conforms to the
SWGDAM guidelines for validating probabilistic genotyping
systems. The district court next stated that TrueAllele had, on
multiple occasions, been peer reviewed and subject to publica-
tion in an “unusually large number” of validation studies and
that no significant scientific evidence suggested the reliability
of TrueAllele had been refuted. Regarding TrueAllele’s error
rate, the district court cited evidence that it had been assessed
through validation studies and information theory comparing
one evidence genotype to the expected distribution of match
statistics. Finally, the district court determined that TrueAllele
had been generally accepted in the relevant scientific commu-
nity because it had been used in over two-thirds of the states
in the United States, it had been used to identify mass casualty
victims of the 2001 terrorist attack on the World Trade Center,
it was used in over 10 cases by the Innocence Project, and 7
crime laboratories were using the software regularly.
Simmer does not contest many of the facts underlying the
district court’s analysis summarized above. Rather, he contends
that the district court ignored other factors that call into ques-
tion the reliability of TrueAllele.
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Simmer, for example, does not and cannot dispute the sig-
nificant number of validation studies in the record concerning
TrueAllele. Instead, he suggests that the validation studies
must be discounted because Perlin is a coauthor of some of
the publications and, as the owner of the company that owns
TrueAllele, has a financial interest in seeing it found reliable.
In other words, Simmer is contending that there are reasons
to question Perlin’s credibility. Even assuming that is true,
an attack on the credibility of an expert witness is not aimed
at the expert’s reasoning or methodology and is thus not the
proper basis for a Daubert/Schafersman challenge. See Smith v.
Colorado Organ Recovery Sys., 269 Neb. 578, 694 N.W.2d 610
(2005) (stating that challenge to expert witnesses’ credibility is
not Daubert/Schafersman claim).
In any event, Perlin’s part in the validation studies was not
as pervasive or unchecked as Simmer suggests. Perlin was
not involved in 10 validation studies in the record. In addi-
tion, six of the studies in which he was listed as an author
were published in peer-reviewed publications. As this court
has previously recognized, “The reason that peer-reviewed
publication is valuable is that it places research in the public
domain and permits evaluation and criticism.” State v. Daly,
278 Neb. 903, 914, 775 N.W.2d 47, 60 (2009). See, also,
Daubert v. Merrell Dow Pharmaceuticals, Inc., 509 U.S. 579,
593, 113 S. Ct. 2786, 125 L. Ed. 2d 469 (1993) (“submission
to the scrutiny of the scientific community is a component
of ‘good science,’ in part because it increases the likelihood
that substantive flaws in methodology will be detected”).
Furthermore, Perlin was not the lone author on any of the
published, peer-reviewed validation studies. That is, other
members of the scientific community also staked their reputa-
tions on the reliability of TrueAllele. We see no basis to say
that the district court abused its discretion by relying on the
validation studies.
Simmer also argues that, apart from Perlin’s involvement in
some of the validation studies, the studies themselves do not
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demonstrate TrueAllele’s reliability. Here, Simmer relies heav-
ily on the testimony of his expert, Adams. Adams acknowl-
edged the studies in the record validating TrueAllele, but
claimed that there is a difference between the “forensic DNA
definition of validation and the software engineering defini-
tion of validation.” Adams emphasized that TrueAllele had not
been tested from a software engineering perspective. In par-
ticular, Adams expressed concerns that the TrueAllele software
source code had not been subjected to independent testing. He
testified that without such a review, confirmation was lacking
as to whether the TrueAllele software actually performs as
described by Perlin.
We do not believe that the district court was required to
find that TrueAllele had been validated “from a software
engineering perspective” to find it reliable. In the Daubert/
Schafersman context, a trial court has discretion to decide what
factors are reasonable measures of reliability in each case. See
Zimmerman v. Powell, 268 Neb. 422, 684 N.W.2d 1 (2004),
citing Kumho Tire Co. v. Carmichael, 526 U.S. 137, 119 S.
Ct. 1167, 143 L. Ed. 2d 238 (1999) (Scalia, J., concurring).
While a review of the TrueAllele source code might also have
confirmed the reliability of TrueAllele, we cannot say that the
district court abused its discretion by relying on the numerous
validation studies confirming the reliability of TrueAllele by
other means. See Com. v. Foley, 38 A.3d 882 (Pa. Super. 2012)
(noting in Frye v. United States, 293 F. 1013 (D.C. Cir. 1923),
analysis of TrueAllele that scientists can validate reliability of
computerized process even if source code underlying process
is unavailable to public). See, also, Edward J. Imwinkelried,
Computer Source Code: A Source of the Growing Controversy
Over the Reliability of Automated Forensic Techniques, 66
DePaul L. Rev. 97 (2016).
Neither are we persuaded by Simmer’s argument that the
validation studies are inadequate because the likelihood ratios
generated by TrueAllele cannot be confirmed as accurate. Here
again, Simmer relies heavily on Adams’ assertions. Adams
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conceded that by running the TrueAllele software on known
DNA profiles, one can determine whether TrueAllele accu-
rately includes or excludes potential contributors. But Adams
asserted that these same studies cannot confirm whether the
specific likelihood ratios are accurate because there is no
“knowable correct output.”
Perlin, however, testified that TrueAllele’s match statistics
can be verified by comparing a broad range of match statistics
to an expected distribution based on probability theory. At
least one of the peer-reviewed validation studies did so and
concluded that there was no significant difference between
TrueAllele’s match statistics and a uniform distribution. The
study concluded that this provided statistical support for the
system’s accuracy. This method of testing may not have dem-
onstrated to an absolute certainty that match statistics gener-
ated by TrueAllele are accurate, but a court performing a
Daubert/Schafersman inquiry should not require absolute cer-
tainty. See, e.g., State v. Herrera, 289 Neb. 575, 856 N.W.2d
310 (2014).
Finally, Simmer argues that the district court failed to
acknowledge the existence of a California study which, Simmer
contends, reported “significant errors” by TrueAllele. Brief for
appellant at 21. This study, however, is not in the record in this
case. Perlin referred to it in his testimony, but he also testified
that it was a “procurement study,” which was never published,
and that the laboratory conducting the study changed the
parameters of TrueAllele so it did not work properly. We do
not see how the district court could have abused its discretion
by declining to rely on a study that was not in the record and
was undermined by Perlin’s unrefuted testimony.
For the reasons we have explained, we disagree with
Simmer’s argument that the district court ignored informa-
tion it was required to consider in determining whether the
TrueAllele evidence was reliable. Neither do we believe the
district court’s ultimate conclusion that the State proved the
reliability of TrueAllele amounted to an abuse of discretion.
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The State adduced significant evidence that TrueAllele is reli-
able. The State presented Perlin’s testimony and copious docu-
mentary evidence describing TrueAllele’s methodology, which
is based on established mathematical principles. SWGDAM
has approved the use of validated and documented probabilistic
genotyping software and provided guidelines for its validation.
TrueAllele has complied with those guidelines: TrueAllele’s
methodology has been repeatedly tested and validated in peer-
reviewed studies.
Even if TrueAllele has not garnered universal acceptance
in the relevant scientific community, that does not automati-
cally disqualify it for admission. See Epp v. Lauby, 271 Neb.
640, 715 N.W.2d 501 (2006). The wide use of TrueAllele by
government crime laboratories and other groups nationwide,
Perlin’s participation in multiple lectures and conferences, and
Helligso’s testimony that the scientific community had agreed
in recent years that programs like TrueAllele are necessary, all
tend to show that TrueAllele has been generally accepted in the
relevant scientific community. Moreover, at least one appellate
court opinion and several trial court orders in our record have
found, based on similar evidence, that TrueAllele has gained
such acceptance. See, e.g., Com. v. Foley, 38 A.3d 882 (Pa.
Super. 2012) (rejecting challenge to TrueAllele, under Frye v.
United States, 293 F. 1013 (D.C. Cir. 1923), standard, which
requires general acceptance in relevant scientific community).
See, also, e.g., State v. Wakefield, 47 Misc. 3d 850, 9 N.Y.S.3d
540 (2015) (same).
3. Application of TrueAllele
in This Case
As mentioned above, some of Simmer’s arguments on
appeal are not directed to the TrueAllele methodology in a
general sense, but instead attack the application of the meth-
odology in this particular case. Specifically, Simmer contends
that two reports, a 2015 validation study conducted by the
Virginia Department of Forensic Science and a 2016 report by
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the President’s Council of Advisors on Science and Technology
(PCAST), suggest that TrueAllele could not be reliably applied
to the particular facts in this case.
While Simmer criticizes the district court for not addressing
his arguments based on these reports, we note that it is not
clear that Simmer adequately raised these arguments in the
district court. Simmer’s pretrial motion in limine challenged
the reliability of TrueAllele evidence, but it did not specifi-
cally raise any concern about whether TrueAllele could prop-
erly be applied to the particular facts of this case. A challenge
to the admissibility of evidence under Daubert/Schafersman
should take the form of a concise pretrial motion. State v.
Herrera, 289 Neb. 575, 856 N.W.2d 310 (2014). It should
identify, in terms of the Daubert/Schafersman factors, what
is believed to be lacking with respect to the validity and reli-
ability of the evidence and any challenge to the relevance of
the evidence to the issues of the case, along with all other
bases for challenging its admissibility. See id. See, also, State
v. Ellis, 281 Neb. 571, 799 N.W.2d 267 (2011). The closest
Simmer’s motion in limine came to raising a challenge to the
application of TrueAllele in this case was its allegation that
the proposed testimony was “based on insufficient facts and
data.” It is far from clear this was specific enough to signal a
challenge to the application of TrueAllele to the facts of this
case. See id.
Even assuming Simmer properly preserved the issue, how-
ever, we see no basis to find that a conclusion that TrueAllele
could be reliably applied to the facts of this case would amount
to an abuse of discretion. To begin, we do not believe the
Virginia validation study demonstrates that TrueAllele could
not be reliably applied in this case. Simmer contends a portion
of that study casts doubt on the conclusions reached in this
case. One section of that study did, based on testing, conclude
that TrueAllele produced a “[p]oor” analysis when the stan-
dard deviation in the mixture weight was less than .03. And,
as Simmer points out, Perlin acknowledged that runs of the
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TrueAllele software yielded a standard deviation below .03 for
the knife handle.
Perlin did not, however, agree with the Virginia study to the
extent it concluded that TrueAllele could not produce a reli-
able analysis when the standard deviation on mixture weights
fell below a certain threshold. He testified that the Virginia
study’s results were “a reflection of the data” the authors ana-
lyzed and that they inappropriately tried to apply “hard and
fast thresholds on statistical parameters” rather than “actu-
ally looking at concordance in the genotypes in their prob-
ability distributions.” Perlin described concordance as similar
results with acceptably small variations across multiple runs
of the software. Perlin’s trial testimony also suggests that the
Virginia laboratory that performed the study eventually came
to hold his view regarding the reliability of TrueAllele even
with a low standard deviation in mixture weights: Perlin tes-
tified that the laboratory now uses TrueAllele “for all their
reported mixtures.”
Even setting aside Perlin’s testimony disagreeing with the
Virginia study’s conclusion as to TrueAllele’s analysis of mix-
ture weights with a standard deviation below .03, the Virginia
study reached that conclusion in the context of testing per-
formed on three-person mixtures. There is no dispute that
the sample from the knife handle in this case is a two-person
mixture. The record does not show that the Virginia study’s
conclusion regarding standard deviation applies to the facts in
this case, much less demonstrates that TrueAllele’s analysis
was unreliable here. Perlin testified that even a 1-percent stan-
dard deviation for the two-person mixture on the knife handle
did not pose a problem for the reliability of the TrueAllele
results.
Simmer’s argument based on the PCAST report fares no
better. Simmer contends that this report found that TrueAllele
was reliable when the minor contributor to a two-person DNA
mixture contributes at least 10 percent of the mixture. Simmer
asserts that because the minor contribution on the knife handle
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in this case was only 2 percent, the PCAST report casts doubt
on the reliability of the TrueAllele analysis in this case. As we
will explain, however, the record before us is murky as to what
the PCAST report concluded, the basis for those conclusions,
and the weight those conclusions deserve.
The PCAST report is not in our record. Unable to cite
directly to the report, Simmer directs us to a Washington trial
court order containing a description of the report. That order
does note that the report concluded that TrueAllele and a simi-
lar software program “appear to be reliable for . . . two person
mixtures where the minor contributor constitutes at least 10%
of the mixture.” The same order, however, summarized several
experts’ criticism of the PCAST report, including its statements
regarding mixture weights. It also observed that the PCAST
report did not cite to any study that supported mixture weight
limitations, a point Perlin also emphasized when he was asked
about the report on cross-examination. The Washington trial
court ultimately denied the defendant’s motion to exclude
TrueAllele evidence despite the fact that the minor contributor
fell below the limitations purportedly expressed in the PCAST
report. With no scientific evidence in the record indicating that
TrueAllele could not generate reliable results under the circum-
stances here, we cannot say that a conclusion that TrueAllele
could reliably be applied to the facts of this case would amount
to an abuse of discretion.
In addition, other evidence in the record did address the
effect that low mixture weights can have on the TrueAllele
analysis, but it did not suggest that TrueAllele’s analysis of low
mixture weights was unreliable. Perlin and the Virginia study
explained that mixture weights are reflected in the match statis-
tic generated by TrueAllele: the lower the mixture weight, the
lower the probability given by the match statistic. Therefore,
the low mixture weight of minor contributor DNA found on
the knife handle was reflected by the finding that the match
between the knife handle and Simmer was 3.71 thousand
times more probable than a coincidental match to an unrelated
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person, a probability much lower than the match between the
doorknob and Simmer (4.22 quintillion times more probable
than a coincidental match to an unrelated person).
The fact that a lower mixture weight makes a match statistic
less certain is not a basis for exclusion of the evidence. We
have previously recognized that DNA analysis is not subject
to exclusion simply because the probability of a match falls
below a certain threshold. See, State v. Tucker, 301 Neb. 856,
920 N.W.2d 680 (2018); State v. Ellis, 281 Neb. 571, 799
N.W.2d 267 (2011). Instead, we have emphasized the need
for DNA analysis to “be accompanied by evidence of the
statistical significance of the findings,” and we have rejected
arguments that jurors are not capable of assigning appropri-
ate weight to those statistics. Tucker, 301 Neb. at 866, 920
N.W.2d at 688. Here, the evidence furnished the jury with the
statistical context to carry out its duty. To the extent the dis-
parity between the major and minor contributor on the knife
handle reduced the certainty of a noncoincidental match, that
was an issue of weight for the jury to consider and not a bar
to admissibility.
We see no basis to conclude that the district court could
not, consistent with our abuse of discretion standard of review,
conclude that TrueAllele could be reliably applied to the par-
ticular facts of this case.
4. Limitations of Our Decision
We conclude by cautioning that this opinion should not be
understood as mandating the admission of TrueAllele evidence
in all future cases. “Daubert . . . does not require that courts
reinvent the wheel each time that evidence is adduced, but it
does permit the re-examination of certain types of evidence
where recent developments raise doubts about the validity of
previously relied-upon theories or techniques.” Schafersman
v. Agland Coop, 262 Neb. 215, 228, 631 N.W.2d 862, 874
(2001). And our Daubert framework “permits re-examination
of the issue if the validity of the prior determination can be
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appropriately questioned.” Schafersman v. Agland Coop, supra.
See, also, State v. Casillas, 279 Neb. 820, 782 N.W.2d 882
(2010). As the instant case demonstrates, “[s]cientific conclu-
sions are subject to perpetual revision” and “hypotheses . . .
that are incorrect will eventually be shown to be so.” Daubert
v. Merrell Dow Pharmaceuticals, Inc., 509 U.S. 579, 597, 113
S. Ct. 2786, 125 L. Ed. 2d 469 (1993). Based on the record
before us in this case, however, we cannot say that the dis-
trict court abused its discretion in allowing admission of the
TrueAllele evidence.
V. CONCLUSION
For the foregoing reasons, we determine that the district
court did not abuse its discretion in admitting DNA analy-
sis conducted by using TrueAllele, over Simmer’s Daubert/
Schafersman challenges. Therefore, we affirm.
Affirmed.