OSAC 2021‐S‐0003

Standards for Determining

Analytical and Stochastic

Thresholds for Application to

Forensic DNA Casework Using

Electrophoresis Platforms

Human Forensic Biology Subcommittee

Biology Scientific Area Committee (SAC)

Organization of Scientific Area Committees (OSAC) for Forensic Science
OSAC 2021‐S‐0003

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OSAC Proposed Standard

OSAC 2021‐S‐0003

Standard for Determining Analytical

and Stochastic Thresholds for

Application to Forensic DNA Casework

Using Electrophoresis Platforms

Prepared by  

Human Forensic Biology Subcommittee

Version: 2.1

December 2023

Disclaimer:

This OSAC Proposed Standard was written by the Human Forensic Biology Subcommittee/Biology

Scientific Area Committee of the Organization of Scientific Area Committees (OSAC) for Forensic

Science following a process that includes an open comment period. This Proposed Standard will

be submitted to a standards developing organization and is subject to change.   

There may be references in an OSAC Proposed Standard to other publications under

development by OSAC. The information in the Proposed Standard, and underlying concepts and

methodologies, may be used by the forensic‐science community before the completion of such

companion publications.  

Any identification of commercial equipment, instruments, or materials in the Proposed Standard

is not a recommendation or endorsement by the U.S. Government and does not imply that the

equipment, instruments, or materials are necessarily the best available for the purpose.

To be placed on the OSAC Registry, certain types of standards first must be reviewed by a

Scientific and Technical Review (STR). The STR process is vital to OSAC’s mission of generating

and recognizing scientifically sound standards for producing and interpreting forensic science

results. The STR shall provide critical and knowledgeable reviews of draft standards or of

proposed revisions of standards previously published by standards developing organizations
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(SDOs) to ensure that the published methods that practitioners employ are scientifically valid,

and the resulting claims are trustworthy.

The STR will consist of an independent and diverse panel, including subject matter experts,

human factors scientists, quality assurance personnel, and legal experts, which will be tasked

with evaluating the proposed standard based on a comprehensive list of science‐based criteria.  

For more information about this important process, please visit our website

at: https://www.nist.gov/topics/organization‐scientific‐area‐committees‐forensic‐

science/scientific‐technical‐review‐panels.  

Version

No.

Issue Date Section Reason

2.0 November 7, 2023  ‐‐  Added to the OSAC Registry and publicly announced.

2.1 December 27, 2023 All Format and font updates only. No content changes made.

   
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Foreword:

The individual minimum requirements for the determination and validation of analytical and

stochastic thresholds are defined in this document. Such thresholds help to ensure credence in

the reliability of the data obtained, while clearly conveying assumptions under which data will be

evaluated during downstream interpretation. The goal is for the laboratory to consistently

produce reliable and reproducible designations of allelic data and identify when allelic drop‐out

may have occurred supported by internal validation data and laboratory protocols.

If a laboratory, as part of its data analysis methods, makes binary determinations regarding the

detection or non‐detection of peaks for casework, analytical thresholds are necessary. Similarly,

if a laboratory, as part of its data analysis methods, makes binary determinations regarding the

potential for allele drop‐out in casework, stochastic thresholds are also necessary.  

Whenever a threshold is applied, it is possible that a classification error may occur.  Intrinsic to

any analytical threshold is the expectation that non‐reproducible noise will produce some peaks

that are incorrectly classified as alleles because they exceed the threshold, and that some true

alleles will be undetected because they produce peaks below the threshold.   Intrinsic to any

stochastic threshold is the expectation that some errors will occur in determining whether allelic

drop‐out may have occurred.  Some heterozygous genotypes will be erroneously classified as

homozygous when the sister allelic peaks drops out and the second peak is above the stochastic

threshold. Conversely, some homozygous genotypes will be erroneously classified as potentially

heterozygous because the single peak is below the stochastic threshold.    The advantage of

determining thresholds based on statistical analysis of relevant empirical data, is that estimates

can be made of the relative risk of these possible errors for a given threshold level.  In setting

thresholds, a statistically based approach must be employed by the laboratory to determine what

proportion of these events are acceptable for the analysis of forensic casework.   

The draft of this standard was developed by the Human Forensic Biology Subcommittee of the

Organization of Scientific Area Committees for Forensic Science.

Keywords: analytical threshold, stochastic threshold, DNA, validation, signal, artifact, noise  
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Table of Contents

1 Scope .....................................................................................................................................6

2 Normative References........................................................................................................... 6

3 Terms and Definitions............................................................................................................ 6

4 Requirements ........................................................................................................................ 9

Annex A.......................................................................................................................................13

   
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Standard for Determining Analytical and Stochastic Thresholds for Application to Forensic

DNA Casework Using Electrophoresis Platforms

1 Scope

These standards set the requirements for forensic laboratories, which as part of their casework

data analysis processes, are making determinations of: a) whether a peak in an electropherogram

represents true signal or might be noise; and b) whether drop‐out of a heterozygous sister allele

to an observed peak either did not occur or might have occurred.

This does not apply to probabilistic genotyping systems that calculate a probability‐based

analytical threshold as a part of its analysis process.

This standard is applicable to forensic short tandem repeat (STR) DNA typing performed on

electrophoresis platforms.  

   

2 Normative References

The following reference isindispensable forthe application ofthe standard. For dated references,

only the edition cited applies. For undated references, the latest edition of the referenced

document (including any amendments) applies.

ANSI/ASB Standard 038, Standard for Internal Validation of Forensic DNA Analysis Methods.

2020. 1st. Ed.

3 Terms and Definitions

For the purposes of this document, the following definitions apply.

3.1

allele

Any of the forms of the same gene that occur at the same locus on a homologous chromosome

but differ in base sequence. ‐ Oorschot, R.A.H. and Ballantyne, K.N. “Capillary Electrophoresis in

Forensic Biology.” Forensic Biology, 49‐57. Elsevier Ltd., Macleod, VIC, Australia, 2013.

3.2   

analytical threshold

The minimum height requirement at and above which detected peaks on a STR DNA profile

electropherogram can be reliably distinguished from instrument background noise; peaks above

this threshold are generally not considered noise and are either artifacts or true alleles. ‐ J.M.

Butler. Fundamentals of Forensic DNA Typing. Elsevier Academic Press, San Diego, CA, 2010.
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3.3    

artifact

A non‐allelic product of the amplification process (e.g., stutter, non‐templated nucleotide

addition, or other non‐specific product), an anomaly of the detection process (e.g., single or

multichannel voltage spikes or “pull‐up”), or a by‐product of primer synthesis (e.g., “dye blob”)

that may be observed on an electropherogram. Some artifacts may complicate the interpretation

of DNA profiles when they cannot be distinguished from the actual allele(s) from a particular

sample. ‐Scientific Working Group on DNA Analysis Methods, SWGDAM Interpretation Guidelines

for Autosomal STR Typing. 2010.

3.4   

control

Material of established origin that is used to evaluate the performance of a test or comparison.

– ASTM E1732‐12 Standard Terminology Relating to Forensic Science. ASTM International, West

Conshohocken, PA, 2012.

3.5

coverage factor (k)

Coverage factor (k factor) (Guide to Uncertainty of Measurement, GUM): numerical factor used

as a multiplier of the combined standard uncertainty in order to obtain an expanded uncertainty.

‐ NISTIR 6919, Recommended Guide for Determining and Reporting Uncertainties for Balances

and Scales, Val Miller, State Laboratory Program, Weights and Measures Division National

Institute of Standards and Technology, Technology Administration, U.S. Department of

Commerce.

3.6   

drop‐out  

(1) Failure of an otherwise amplifiable allele to produce a signal above analytical threshold

because the allele was not present or was not present in sufficient quantity in the aliquot that

underwent polymerase chain reaction (PCR) amplification. (2) A hypothesis/postulate for the

failure to observe one or more allelic peaks in an electropherogram that are expected for the

assumed contributor(s) to a sample. – Scientific Working Group on DNA Analysis Methods,

SWGDAM Guidelines for STR Enhanced Detection Methods. Scientific Working Group on DNA

Analysis Methods, 2014.

3.7   

empirical data

Factual data that are based on actual measurement, observation, or direct sensory experience

rather than on theory. – NFPA 921 Guide for Fire and Explosion Investigations. NFPA, 1

Batterymarch Park, Quincy, MA 02169‐7471, 2014.
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3.8

internal validation

The accumulation of test data within the laboratory for developing the laboratory standard

operating procedures and determining the limits of the method(s). Internal validation

demonstrates that the established protocols for the technical steps of the test and for data

interpretation perform as expected in the laboratory. ‐ ANSI/ASB Standard 038, 1st. Ed. 2020.

3.9   

locus (loci)

A unique physical location of a gene (or specific sequence of DNA) on a chromosome; the plural

of locus is loci (which is pronounced low‐sigh). – J.M. Butler. Fundamentals of Forensic DNA

Typing. Elsevier Academic Press, San Diego, CA, 2010.

3.10   

noise

Meaningless output occurring in electronic equipment; it is random electronic variation that is

generated by and intrinsic to the electronic circuitry. It ultimately establishes the smallest

analytical signal that can be quantitatively measured with confidence. A part of a signal that is

not the target signal.  ‐ ASB Technical Report 025 Crime Scene/Death Investigation – Dogs and

Sensors Terms and Definitions. AAFS Academy Standards Board (ASB), 2017.

3.11

peak

The visual image of an allele or other fluorescent signal on an electropherogram; for an allele,

the peak height (Y axis) representsthe amount of amplified DNA in the PCR and the peak position

(X axis) represents the fragment length.  ‐ J.M. Butler. Fundamentals of Forensic DNA Typing.

Elsevier Academic Press, San Diego, CA, 2010.

3.12   

stochastic threshold  

The peak height value in a DNA electrophoretic profile above which it is reasonable to assume

that, at a given locus, allelic dropout of a sister allele in a heterozygous pair has not occurred in

a single source DNA sample; due to the possibility of shared alleles in mixed samples, the

presence of allele peaks above the stochastic threshold is no guarantee that allele dropout did

not occur in mixed DNA sample profiles. ‐ Scientific Working Group on DNA Analysis Methods,

SWGDAM Interpretation Guidelines for Autosomal STR Typing. 2010.
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3.13   

stutter

An artifact of PCR amplification typically observed one or more repeat unitssmaller or larger than

an STR allele in a DNA electrophoretic profile, may result from strand slippage during PCR

amplification. A stutter peak is generally of lower relative fluorescent units (RFU) than the allele

peak. ‐ Scientific Working Group on DNA Analysis Methods, SWGDAM Interpretation Guidelines

for Autosomal STR Typing. 2010.

4 Requirements

4.1 The laboratory shall have an analytical threshold1 for each electrophoresis platform (e.g.,

distinct capillary electrophoresis (CE) models) used in casework that is established and tested

using data generated during internal validation.

NOTE: When multiple instruments of the same kind/model/platform are used for casework, data

generated from each instrument should be considered due to potential variations in noise

inherent to each instrument.

4.1.1 The laboratory shall determine and document the acceptable proportion of noise peaks

that will exceed the analytical threshold (e.g., as reflected by the number of standard deviations

above the noise mean [RFU]). This establishes the laboratory’s predetermined expectation for

acceptable performance of the analytical threshold.  

NOTE: Asthe number ofstandard deviationsincreases, the potential for allele non‐detection also

increases.  Recognizing there is a tradeoff between the risk of allele non‐detection and the risk

of mistakenly labeling noise peaks as alleles, the analytical threshold should be set such that the

probability that noise exceeds the analytical threshold is between 10‐2 and 10‐6 (e.g., k=2 to k=5).  

See Table 9 (Mönich et al., page 115) relating k value to probability that a randomly generated

noise peak exceeds the analytical threshold. 2  

4.1.2 The laboratory shall establish and verify an analytical threshold based on internally

generated empirical data acquired from the same electrophoresis platform, analysis software

and DNA profiling chemistry utilized in casework.   

4.1.2.1 Validation studies used to establish an analytical threshold shall include samples of

known composition (e.g., known genotype and negative controls3). Casework samples shall not

be used to determine an analytical threshold.

1 This does not apply to the dye channel used for the internal size standard.   

2 Mönich, U.J., Duffy, K., Medard, M., Cadambe, V., Alfonse, L.E. and Grgicak C. "Probabilistic characterisation of

baseline noise in STR profiles." Forensic Science International: Genetics 19 (2015): 107‐122.   

3 Negative amplification and Reagent blank controls are acceptable sample types providing that they contain no

indication of amplified product.
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4.1.2.2 Acceptable positions on an electropherogram to interrogate when establishing analytical

thresholdsshall be those that exclude possible allele or artifact peaks of known origin (e.g., alleles

and associated stutter products such as n‐1, n‐2, and n+1 positions, spectral pull‐up peaks

including those due to internal size standard, voltage spikes, unincorporated dye peaks).   

4.1.2.3 When modifications to the instrument are made that have the potential to impact the

noise output of the instrumentation, the performance of the analytical threshold shall be verified

and documented (e.g., performance check following change in laser and/or recalibration of the

instrument).

4.1.3 The laboratory shall assess statistically‐based analytical thresholds for each dye channel.

A number of statistical methods to establish analytical threshold(s) have been described in the

scientific literature.4   Relevant references are provided in Annex A Bibliography. Laboratories

employing a single global analytical threshold for all dye channelsshall provide statisticalsupport

(e.g., based on 1‐way analysis of variance [ANOVA]showing no statistically significant differences

[p<0.05] in noise across dye channels).   

4.1.4 If the laboratory employs rounding (e.g., to the nearest unit of 5 or 10 RFU), the

implications of this rounding regarding the chance of mistaking noise for signal and the chance

of not labeling a true allele in low template samples shall be documented.

4.2 The laboratory shall have a stochastic threshold5 for each electrophoresis platform (e.g.,

distinct CE models and DNA profiling chemistry) used in casework that is established and verified

using data generated during internal validation.

NOTE: When multiple instruments of the same kind/model/platform are used for casework, data

generated from each instrument shall be evaluated to identify potential variations inherent to

each instrument.

4.2.1 The laboratory shall determine and document the acceptable proportion of false

homozygotes (drop‐out) that will appear above the stochastic threshold (e.g., as reflected by the

number ofstandard deviations above the mean). This establishesthe laboratory’s predetermined

expectation for acceptable performance of the stochastic threshold.  

NOTE: As the number of standard deviations increases, the potential for true homozygote

detection decreases.  Recognizing there is a tradeoff between detecting true homozygotes and

the risk of mistakenly labeling a heterozygote with drop‐out as a homozygote, the stochastic

threshold should be set such that the probability that drop‐out exceeds the stochastic threshold

is between 10‐2 and 10‐6 (e.g., k=2 to k=5).

4 Methods based on an extreme value calculation (e.g., 2X peak to trough difference) do not address the statistical

confidence of a given analytical threshold.  In addition, such methods can be easily skewed by outlier data and thus

do not meet the requirements of this standard.      

5 Determination of a stochastic threshold does not apply to the dye channel used for the internal size standard. 
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4.2.2 The laboratory shall establish a stochastic threshold based on internally generated

empirical data acquired from the same electrophoresis platform, analysis software, and DNA

profiling chemistry utilized in casework.    

NOTE: Though laboratories using probabilistic genotyping systems are not required to establish

or apply stochastic thresholds, they are still required to conduct validation studies that inform

the laboratory of stochastic issues (e.g., allele drop‐out).  

4.2.3 Validation studies of allelic drop‐out used to establish a stochastic threshold shall include

dilution series of single source samples of known genotype with a high level of heterozygosity

and a range of differences in sister allele separation within each locus. The dilution series shall

include DNA quantities around which allelic drop‐out is likely to occur.

NOTE: The use of larger data sets improves the accuracy of the stochastic threshold.  Stochastic

events are, by definition, random.   

4.2.4 If processes are utilized to increase or decrease sensitivity (e.g., changes to amplification

cycle number, injection time, and post‐amplification purification or concentration of amplified

products), the laboratory shall perform additional studies to determine the appropriate

stochastic threshold(s) for the method(s) employed.

NOTE: For any profile generated using a reduced sensitivity method, where all interpreted peaks

remain above the default stochastic threshold, the laboratory may evaluate whether or not the

stochastic threshold implemented for routine data analysis is applicable to the decreased

sensitivity method.   

4.2.5 A number of methods to calculate a stochastic threshold have been described in the

scientific literature. Relevant references are provided in Annex A Bibliography. The method

selected must be supported by both the scientific literature and empirical data generated during

internal validation by the laboratory.6 The laboratory shall document the desired level of

statistical confidence (e.g., as reflected by the number of standard deviations above the mean)

for establishing a stochastic threshold.

4.3 Following the completion of the laboratory’s internal validation study, all data, data

analyses, and calculations used to determine the analytical and stochastic thresholds shall be

documented in the final validation report.    

6

Methods based on the largest surviving allele do not directly address the probability of allele drop‐out at the

stochastic threshold. Therefore, these methods are not recommended for determining a stochastic threshold.  

Thresholds shall be established based on statistical analysis, and skewed (i.e., non‐symmetrical) data must be

appropriately transformed prior to further analysis. 
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4.3.1 The validation report shall include the following information:

a) a record of predetermined specifications and quality attributes (i.e.,statistical confidence

level/error rate7

) for accepting and implementing the thresholds(s) into operations.  

b) a description of the samples, test methods, electropherograms and data used to calculate

the threshold(s).

c) any formulae or theory applied to compute the thresholds.  

d) reference literature as appropriate.

4.3.2 The validation report, all data, data analyses, and calculations used to determine the

analytical and stochastic thresholds shall be maintained by the laboratory.  

5 Conformance

Documented conformance to these requirements needs to be: (1) approved by the laboratory’s

DNA Technical Leader or other appropriate personnel (2) communicated to all analysts during

training, and (3) made readily available for review (e.g., by auditors or inspectors, stakeholders

who use reports generated by the laboratory, etc.).

To demonstrate conformance with this standard, the laboratory shall meet the requirements in

the ANSI/ASB Standard 038, Standard for Internal Validation of Forensic DNA Analysis Methods.

2020. 1st. Ed.

   

7 Type 1 Error, the rejection of a true null hypothesis(e.g., a 99% confidence level has a 1% error rate).  In the context

of the analytical threshold, this represents the probability that an instrument noise peak will exceed the analytical

threshold. In the context of the stochastic threshold, this represents the probability that a true heterozygous peak

will exceed the stochastic threshold while the sister allele has dropped out.
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Annex A

(informative)

Bibliography

1] Gilder, J., Doom, T., Inman, K. and Krane, D.  Run‐specific limits of detection and quantitation

for STR‐based DNA testing. J For. Sciences, 2007, 52:(1):97‐101.

2] Bieber, F.R., Buckleton, J.S., Budowle, B., Butler, J.M. and Coble, M.D. "Evaluation of forensic

DNA mixture evidence: protocol for evaluation, interpretation, and statistical calculations

using the combined probability of inclusion." BMC genetics 17.1 (2016): 125.

3] Butts, E.L., Kline, M., Duewer, D., Hill, C., Butler, J.M. and Vallone, P. "NIST validation studies

on the 3500 Genetic Analyzer." Forensic Science International: Genetics Supplement Series 3.1

(2011): e184‐e185.

4] Gill, P., Puch‐Solis, R. and Curran, J. "The low‐template‐DNA (stochastic) threshold—its

determination relative to risk analysis for national DNA databases." Forensic Science

International: Genetics 3.2 (2009): 104‐111.

5] Mönich, U.J., Duffy, K., Medard, M., Cadambe, V., Alfonse, L.E. and Grgicak C.   "Probabilistic

characterisation of baseline noise in STR profiles." Forensic Science International: Genetics 19

(2015): 107‐122.

6] Puch‐Solis, R., Kirkham, A.J., Gill, P., Read, J., Watson, S. and Drew, D. "Practical determination

of the low template DNA threshold." Forensic Science International: Genetics 5.5 (2011): 422‐

427.

7] Rowan, K.E., Wellner, G.A. and Grgicak, C.M. "Exploring the impacts of ordinary laboratory

alterations during forensic DNA processing on peak height variation, thresholds, and

probability of dropout." Journal of forensic sciences 61.1 (2016): 177‐185.

8] Federal Bureau of Investigations Quality Assurance Standards (QAS) for Forensic DNA Testing

Laboratories    https://www.fbi.gov/file‐repository/quality‐assurance‐standards‐for‐forensic‐

dna‐testing‐laboratories.pdf

9] NISTIR 6919, Recommended Guide for Determining and Reporting Uncertainties for Balances

and Scales, Val Miller, State Laboratory Program, Weights and Measures Division

National Institute of Standards and Technology, Technology Administration, U.S. Department

of Commerce.