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NISTIR 8351-DRAFT

EXECUTIVE SUMMARY

DNA Mixture Interpretation:

A NIST Scientific Foundation Review

John M. Butler

Hari Iyer

Rich Press

Melissa K. Taylor

Peter M. Vallone

Sheila Willis*

*International Associate under contract; retired director of Forensic Science Ireland

The full report is available free of charge from:

https://doi.org/10.6028/NIST.IR.8351-draft
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Executive Summary

All scientific methods have limits. One must understand those limits to use a method 

appropriately. This is especially important in forensic science as critical decisions impacting life 

and liberty are often based on the results of forensic analysis. 

Forensic DNA technology brings immense benefits to society, and new tools and techniques can 

increase those benefits further. But as new technologies are implemented with increased 

detection capabilities, we believe it is important to periodically assess their impacts on the 

scientific discipline. We do so in this scientific foundation review by identifying scientific 

principles, reviewing the scientific literature, gathering other empirical evidence from publicly 

available sources, and receiving input from a group of forensic DNA practitioners and 

researchers. This scientific foundation review explores what is known about the limits of DNA 

mixture interpretation methods, including probabilistic genotyping software systems.

As with any field, the scientific process (research, results, publication, additional research, etc.) 

continues to lead to advancements and better understanding. Information contained in this report 

comes from the authors’ technical and scientific perspectives and review of information available 

to us during the time of our study. Where our findings identify opportunities for additional 

research and improvements to practices, we encourage researchers and practitioners to take 

action toward strengthening methods used to move the field forward. The findings described in 

this report are meant solely to inform future work in the field.

Improvements in DNA testing methods have allowed forensic scientists to reduce the quantity of 

DNA required for profiling an individual. In the 1990s, an evidence sample needed to contain 

thousands of cells, such as from a visible blood or semen stain. Today, analysts can extract a 

DNA profile from the few skin cells that someone might leave behind when handling an object.

This increased sensitivity extended the usefulness of DNA analysis into new areas of criminal 

activity beyond homicides and sexual assaults. DNA on bullets or cartridge casings can reveal 

clues to crimes involving firearms. Swabbing objects that a perpetrator might have handled can 

yield evidence in property crimes. Cold case evidence previously analyzed with less 

discriminating methods can be re-opened and researched again to find new insights. 

However, because people constantly shed small amounts of DNA into the environment, and by 

touching objects, people can potentially transfer small amounts of DNA from one surface to 

another, including someone else’s DNA. Analyzing small quantities of DNA can create 

challenges in interpreting the data. 

Highly sensitive methods, now universally used across the forensic DNA community, often 

detect DNA from more than one individual in a sample. But distinguishing one person’s DNA 

from another in these mixtures, estimating how many individuals contributed DNA, determining 

whether the DNA is even relevant or is from contamination, or whether there is a trace amount of 

suspect or victim DNA make DNA mixtures inherently more challenging to interpret than singlesource samples. These issues, if not properly considered and communicated, can lead to 

misunderstandings regarding the strength and relevance of the DNA evidence in a case.
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When laboratories analyze high-quality, single-source samples, decision-makers often have 

confidence in DNA test results in part because it has been demonstrated that different 

laboratories will arrive at the same result. This is true regardless of the specific instruments, kits, 

and software used. However, multiple interlaboratory studies conducted by different groups over 

the past two decades have demonstrated a wide range of variation in how specific DNA mixtures

are interpreted.

This report is arranged into six chapters and two appendices. Chapter 1 introduces the topic of 

DNA mixtures (samples that contain DNA from more than one individual), the difficulties 

behind their interpretations, and the relevance of the issues explored in the other chapters of this 

scientific foundation review. Chapter 2 provides background information on DNA and describes 

principles and practices underlying mixture measurement and interpretation. The likelihood ratio 

(LR) framework and probabilistic genotyping software (PGS) are also discussed. Chapter 3 lists 

data sources used in this study and strategies to locate them. Chapters 4 and 5 cover the report’s 

core concepts: reliability and relevance issues in DNA mixture interpretation. Chapter 6 explores 

the potential of new technologies to assist mixture interpretation and considerations for 

implementation. The two appendices provide context on how the field has progressed and 

strategies to strengthen it going forward. Appendix 1 presents the history of DNA mixture 

interpretation, while Appendix 2 considers various perspectives on training and continuing 

education.

A DNA Mixture Resource Group (see Table 1.2), with extensive experience in public and private 

forensic DNA laboratories, reviewed an early draft of our report and provided valuable feedback, 

insights, and suggestions. However, they were not asked to sign off on our final report or endorse 

its conclusions. The NIST team is grateful for their dedication and contributions to our efforts. 

Chapter 1: Introduction

New tools and techniques for analyzing and interpreting minor contributors to DNA mixtures are 

now routinely employed in everyday casework in the United States and around the world. These 

tools include DNA profiling kits, genetic analyzer instruments, and probabilistic genotyping 

software. 

DNA mixtures can be partly understood by analogy to latent print examination. If multiple 

fingerprints are deposited on top of one another, it would be difficult to tease apart the individual 

fingerprints because it may not be clear which ridge lines belong to which print. In a DNA 

mixture it may not be clear which genetic components, called alleles, belong to which 

contributor. Interpreting the mixture requires an assessment of which alleles go together to form 

the DNA profiles of the individual contributors.

Forensic scientists interpret DNA mixtures with the assistance of statistical models and expert 

judgment. Interpretation becomes more complicated when contributors to the mixture share 

common alleles. Complications can also arise when random variations, also known as stochastic 

effects, make it more difficult to confidently interpret the resulting DNA profile.
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Not all DNA mixtures present these types of challenges. We agree with the President’s Council

of Advisors on Science and Technology (PCAST) that “DNA analysis of single-source samples 

or simple mixtures of two individuals, such as from many rape kits, is an objective method that 

has been established to be foundationally valid” (PCAST 2016). Therefore, this scientific 

foundation review does not concentrate on interpretation of single-source DNA samples and twoperson mixtures involving significant quantities of DNA from both contributors. 

Instead, this review focuses on methods for interpreting data from complex DNA mixtures, 

which we define as samples that contain comingled DNA from two or more contributors in 

which stochastic effects or allele sharing cause uncertainty in determining contributor genotypes. 

The following factors contribute to increased complexity (see also Chapter 2):

• Number of contributors and the degree of overlapping alleles

• Low-quantity DNA from one or more minor contributors 

• Degree of degradation or inhibition of the DNA sample.

It is important that users of forensic DNA test results understand that DNA evidence can vary 

greatly in complexity based on these factors, and that more complex samples involve greater 

uncertainty.

Chapter 2: DNA Mixture Interpretation: Principles and Practices

Successful analysis and interpretation of DNA results depends on crime scene evidence (the “Q” 

or questioned sample) being of suitable quality and quantity, and the availability of a reference 

sample (the “K” or known sample). When appropriate Q and K DNA profiles are available, 

forensic scientists can perform a Q-to-K comparison and report a likelihood ratio (LR) that is an 

evaluative interpretation of the strength of this association using specific assumptions and 

usually one of several statistical approaches. In testing forensic casework samples, a range of 

DNA profile qualities and quantities can exist. DNA mixtures are inherently more difficult to 

interpret than single-source DNA samples.

The process of DNA evidence analysis can be divided into two major steps: (1) measurements of 

relative abundances of polymerase chain reaction (PCR) products in a tested DNA sample that 

are displayed as an electropherogram (EPG), and (2) interpretation involving use of the EPG 

data to make a strength-of-evidence assessment when an evidentiary DNA profile is compared to 

a person of interest (POI). The outcome of interpretation includes an LR number that can range 

in value depending on the analyst’s assumptions, protocols, algorithms, tools, and other 

variables. There remains a need to assess the fitness for purpose of an analyst’s LR using 

empirical methods.

Forensic scientists interpret DNA mixtures with the assistance of statistical models and expert 

judgment. Interpretation becomes more complicated when contributors to the mixture share 

common alleles. Complications can also arise when reduced DNA template amounts are used in 

PCR, where random sampling, also known as stochastic effects, makes it more difficult to 

confidently interpret the resulting DNA profile. 
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This chapter describes 16 principles and includes 6 key takeaways.

KEY TAKEAWAY #2.1: DNA mixtures, where the DNA of more than one individual is 

present in a sample, are inherently more difficult to interpret than single-source DNA 

samples.

KEY TAKEAWAY #2.2: Generating a DNA profile involves measuring the inherent 

physical properties of the sample. Interpreting a DNA profile involves assigning values that 

are not inherent to the sample. To do this, the DNA analyst uses their judgment, training, 

tools (including computer software), and experience, and considers factors such as case 

context.

KEY TAKEAWAY #2.3: The process of generating a DNA profile can produce stochastic 

or random variation and artifacts that contribute to the challenge of DNA mixture 

interpretation.

KEY TAKEAWAY #2.4: DNA mixtures vary in complexity, and the more complex the 

sample, the greater the uncertainty surrounding interpretation. Factors that contribute to 

complexity include the number of contributors, the quantity of DNA from each 

contributor, contributor mixture ratios, sample quality, and the degree of allele sharing. 

KEY TAKEAWAY #2.5: Continuous probabilistic genotyping software (PGS) methods 

utilize more information from a DNA profile than binary approaches.

KEY TAKEAWAY #2.6: Likelihood ratios are not measurements. There is no single, 

correct likelihood ratio (LR). Different individuals and/or PGS systems often assign

different LR values when presented with the same evidence because they base their 

judgment on different kits, protocols, models, assumptions, or computational algorithms. 

Empirical data for assessing the fitness for purpose of an analyst’s LR are therefore

warranted.

Chapter 3: Data and Information Sources

This chapter contains sources of data and information used in conducting this review along with 

strategies to locate them. These sources include (1) peer-reviewed articles appearing in scientific 

journals, (2) published interlaboratory studies, (3) laboratory internal validation study summaries

that are accessible online, and (4) proficiency test data available on test provider websites. 

Chapter 4: Reliability of DNA Mixture Measurements and Interpretation

In this report, we divide the challenges presented by DNA mixtures into two main categories. 

The first involves the reliability of mixture interpretation methods when used with DNA 

evidence of varying complexity. (Chapter 5 deals with the second challenge: relevance.) In this 

report, we use the “plain English” definition of reliability as a measure of trustworthiness. A 

highly reliable method is one that consistently produces accurate results. Reliability is not a yes 

or no question, but a matter of degree. Understanding the degree of reliability of a method can 
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help the user of that information decide whether they should trust the results of that method when 

making important decisions. 

This chapter considers foundational issues related to reliability of DNA mixture interpretation. 

Reliability centers on trustworthiness established through empirical assessments of available data 

to evaluate the degree of reliability of a system or its components. We use the term “factor 

space” to describe the factors that influence complexity, measurement, and interpretation 

reliability – these factors include the number of contributors, the degree of allele sharing, the 

ratios of mixture components, and the amount and quality of the DNA tested. 

We note that the degree of reliability of a DNA mixture interpretation system, such as a DNA 

analyst using a probabilistic genotyping software program, depends on sample complexity. 

Results cannot be simply categorized as “reliable” or “unreliable” without considering context. 

In addition, reliability cannot be established without validation tests using known samples of 

similar complexity. The results of such tests provide data that are considered accurate and 

reliable; only with such valid results can comparisons be made as to the reliability of unknown 

casework samples. We also emphasize that samples used in proficiency tests need to be 

representative of complex DNA mixtures seen in casework if these tests are intended to assess 

analysts’ ability to conduct dependable DNA mixture interpretation.

Finally, the theme of reliability is discussed throughout this report. Note that our original goal in 

this review was external and independent assessment of reliability based on publicly available 

data that met our selection criteria. These criteria evolved during this study as we became aware 

of the amount and type of data available to us. Laboratories and researchers may make claims or 

have their own understanding of reliability as it relates to their own work, but our findings are 

defined by the public information available at the time of this report. 

This chapter includes eight key takeaways.

KEY TAKEAWAY #4.1: The degree of reliability of a component or a system can be 

assessed using empirical data (when available) obtained through validation studies, 

interlaboratory studies, and proficiency tests.

KEY TAKEAWAY #4.2: To enable effective use of any information, responsibilities exist 

with both providers and users of that information. While a provider explains the relevance 

and significance of the information and data, only the user can assess the degree of 

reliability, validity, and whether that information is fit-for-purpose.

KEY TAKEAWAY #4.3: Currently, there is not enough publicly available data to enable 

an external and independent assessment of the degree of reliability of DNA mixture 

interpretation practices, including the use of probabilistic genotyping software (PGS) 

systems. To allow for external and independent assessments of reliability going forward, we 

encourage forensic laboratories to make their underlying PGS validation data publicly

available and to regularly participate in interlaboratory studies.
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KEY TAKEAWAY #4.4: Additional PGS validation studies have been published since the 

2016 PCAST Report. However, publicly available information continues to lack sufficient 

details needed to independently assess reliability of specific LR values produced in PGS 

systems for complex DNA mixture interpretation. Even when a comparable reliability can 

be assessed (results for a two-person mixed sample are generally expected to be more 

reliable than those for a four-person mixed sample, for example), there is no threshold or 

criteria established to determine what is an acceptable level of reliability.

KEY TAKEAWAY #4.5: Current proficiency tests are focused on single-source samples 

and simple two-person mixtures with large quantities of DNA. To appropriately assess the 

ability of analysts to interpret complex DNA mixtures, proficiency tests should evolve to 

address mixtures with low-template components or more than two contributors – samples 

of the type often seen in modern casework.

KEY TAKEAWAY #4.6: Different analysts and different laboratories will have different 

approaches to interpreting the same DNA mixture. This introduces variability and 

uncertainty in DNA mixture interpretation. Improvements across the entire community 

are expected with an increased understanding of the causes of variability among 

laboratories and analysts.

KEY TAKEAWAY #4.7: The degree of reliability of a PGS system when interpreting a 

DNA mixture can be judged based on validation studies using known samples that are 

similar in complexity to the sample in the case. To enable users of results to assess the 

degree of reliability in the case of interest, it would be helpful to include these validation 

performance results in the case file and report.

KEY TAKEAWAY #4.8: We encourage a separate scientific foundation review on the topic 

of likelihood ratios in forensic science and how LRs are calculated, understood, and 

communicated.

Chapter 5: Context and Relevance Related to DNA Mixture Interpretation

The second major challenge posed by DNA mixtures involves the relevance of a DNA sample to 

the crime being investigated. The question of relevance arises because DNA can be transferred 

between surfaces, potentially more than once. This means that some of the DNA present at a 

crime scene may be irrelevant to the crime, and current DNA profiling methods increase the 

likelihood of detecting more DNA. Similarly, today’s highly sensitive DNA methods increase 

the risk that very small amounts of contamination might affect DNA test results. 

Chapter 5 focuses on questions of context and relevance: How and when was the DNA 

deposited, and is that DNA relevant to the crime being investigated? 

The question of relevance arises because people readily shed DNA into the environment, and 

they can potentially transfer DNA between surfaces when touching objects or other people. 

Therefore, the DNA present at a crime scene or on a piece of evidence may be irrelevant to any 

crime. To assess relevance, in addition to knowing specific details of the case, one would need 
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information on what factors make DNA more or less likely to transfer and to persist in the 

environment. This chapter reviews the scientific literature on DNA transfer and persistence and 

presents strategies for assessing DNA relevance. 

The fact that DNA can be transferred between surfaces upon contact is a foundational principle 

of forensic DNA analysis. This is what makes the discipline useful for investigating crimes in the 

first place. This has several implications for DNA found at a crime scene. First, that DNA might 

have been deposited before or after the crime was committed and therefore may not be relevant 

to the crime. Second, the DNA might have been deposited via secondary transfer, which occurs 

when DNA is picked up for one surface and deposited on another. For instance, a person might 

pick up DNA from a second person during a handshake, then deposit the second person’s DNA 

onto an item or surface. 

These possibilities mean that the presence of a person’s DNA in an evidence sample does not 

necessarily mean that the DNA is relevant to the crime. Relevance should be assessed. If not, the 

evidence can be misleading. 

By definition, highly sensitive methods are more likely to detect small quantities of DNA, 

including background DNA that may be present in the environment. In addition, highly sensitive 

methods are more likely to detect DNA mixtures, which by their nature usually include irrelevant 

DNA. Therefore, when assessing evidence that involves very small quantities of DNA, it is 

especially important to carefully consider relevance.

This report uses the word contamination to describe the transfer of irrelevant DNA during an 

investigation. For example, a fingerprint brush can potentially transfer minute amounts of DNA 

onto evidence at a crime scene. Such a small amount of DNA might have gone undetected in the 

past, but highly sensitive methods increase the likelihood that it might now be detected. This 

increases the likelihood that contamination might affect an investigation.

Forensic laboratories have been using procedures to avoid contamination since the advent of 

DNA methods. However, because the likelihood of detecting contaminating DNA has increased 

with the development of highly sensitive DNA methods, contamination avoidance in forensic 

laboratories is more important than ever. Furthermore, contamination avoidance procedures 

should be used during all stages of an investigation, including at the crime scene. Elimination 

databases that include DNA profiles of laboratory staff and police who go to crime scenes can 

help identify contamination and should be maintained.

Many interpretation methods, including probabilistic genotyping, address questions about who 

might have contributed DNA to a crime scene profile and express the strength of evidence in the 

form of a likelihood ratio. This statistic does not provide any information about how much DNA 

was present, or how or when the DNA was deposited. For instance, a large blood stain might 

produce a very similar likelihood ratio to a swab from a light switch, yet the two types of 

evidence might vary greatly in terms of their evidential value. Therefore, the likelihood ratio 

should not be used in isolation. It is imperative that the likelihood ratio be considered in the 

context of other evidence in the case.
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The fact that DNA can transfer does not mean that DNA is useless as evidence. To the contrary, 

this is what makes DNA useful to criminal investigations in the first place. However, the 

possibility of DNA transfer may raise questions of relevance that need to be addressed, 

especially in cases that involve very small amounts of DNA. These questions can be addressed 

by considering DNA evidence in the context of case circumstances, including other evidence in 

the case.

More research is needed on DNA transfer and persistence. In addition, to make use of the studies 

that are available, individual laboratories would need to know how the sensitivity of methods 

used in their laboratory compares to the sensitivity of methods employed in the studies being 

considered.

This chapter includes six key takeaways.

KEY TAKEAWAY #5.1: DNA can be transferred from one surface or person to another, 

and this can potentially happen multiple times. Therefore, the DNA present on an evidence 

item may be unrelated (irrelevant) to the crime being investigated.

KEY TAKEAWAY #5.2: Highly sensitive DNA methods increase the likelihood of 

detecting irrelevant DNA. When assessing evidence that involves very small quantities of 

DNA, it is especially important to consider relevance.

KEY TAKEAWAY #5.3: Highly sensitive methods increase the likelihood of detecting 

contaminating DNA that might affect an investigation. Contamination avoidance 

procedures should be robust both at the crime scene and in the laboratory.

KEY TAKEAWAY #5.4: DNA statistical results such as a sub-source likelihood ratio do 

not provide information about how or when DNA was transferred, or whether it is relevant

to a case. Therefore, using the likelihood ratio as a standalone number without context can 

be misleading. 

KEY TAKEAWAY #5.5: The fact that DNA transfers easily between objects does not 

negate the value of DNA evidence. However, the value of DNA evidence depends on the 

circumstances of the case.

KEY TAKEAWAY #5.6: There is a growing body of knowledge about DNA transfer and

persistence, but significant knowledge gaps remain.

Chapter 6: New Technologies: Potential and Limitations

New technologies are often investigated to assess whether they can provide solutions to existing 

problems in the forensic community. The adoption and implementation of these technologies 

depends upon a cost/benefit analysis within forensic laboratories. Appreciating fundamental 

challenges with DNA mixture interpretation can assist in considering whether new approaches 

can bring desired improvements to mixture interpretation.
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The ability to analyze short tandem repeat alleles by sequence in addition to length promises to 

bring some new capabilities to forensic DNA laboratories, including the potential for 

improvements in DNA mixture interpretation. Next-generation sequencing platforms also enable 

additional genetic markers to be examined, some of which, such as microhaplotypes, have been 

pursued with the potential to improve DNA mixture interpretation. Additionally, cell separation 

techniques offer the potential to separate contributors prior to DNA extraction.

The ultimate decision to implement new technologies in forensic laboratories should be driven 

by a real-use case and by those responsible for producing and reporting the information. A 

vendor or members of the general public may encourage forensic DNA laboratories to adopt a 

new approach or technology without appreciating investments required to make a change. 

Consideration should be given to whether supporting factors and resources will be available 

upon implementation (e.g., allele frequencies, analysis software, interpretation methods, training, 

and support for potential admissibility hearings). An overall assessment of 1) how a new 

technology works, 2) what its limitations are, and 3) how it might specifically address the 

problem to be solved (e.g., DNA mixture interpretation) is important and a key component of 

evaluating whether implementation will be worthwhile.

This chapter includes two key takeaways.

KEY TAKEAWAY #6.1: Fundamental measurement and interpretation issues 

surrounding DNA mixtures, as described in Chapter 2, should be understood before 

attempting to apply a new technology.

KEY TAKEAWAY #6.2: Implementation requires a thorough understanding of the 

benefits and limitations of the new technology as well as the practical investment of time 

and effort put forth for its adoption by the laboratory. 

To read the entire report, which is available free of charge, 

see https://doi.org/10.6028/NIST.IR.8351-draft