The NFI experience with the 

statistical evaluation of 

complex DNA mixtures.

Ate Kloosterman 

Netherlands Forensic Institute1 & 

University of Amsterdam2

May 28 2014 

a.kloosterman@nfi.minvenj.nl 
18 May 2011 

DNA profile comparison 

NFI approach: result of a DNA profile comparison is categorized to 

one of four categories 

• A: Exclusion 

• B: Match with statistical interpretation 

• C: Match without statistical interpretation 

• D: No exclusion or match; subdivided into: 

D1: Cannot be excluded 

D2: Inconclusive 

Definition of a DNA match (categories B and C): 

“it can be concluded, that all the alleles of the reference profile are also 

present in the defined DNA profile of the evidence”. 
18 May 2011 

Category B: match with statistical interpretation 

D3S1358 vWA D16S539 D2S1338

Evidence 15 16 18 13 16 17 11 12 13 14 16 17 23

Suspect 15 18 13 16 11 14 17 23 

• DNA profile suspect matches mixed DNA profile evidence 

• The assumption that all alleles of all donors are present in the mixed DNA profile 

 of the evidence can be safely made 
18 May 2011 

DNA profile comparison and evidential value 

Category B: Match with statistical interpretation 

•Matching DNA profiles: determine whether the evidential 

value of the match can be evaluated statistically. 

•Condition: the determination or assumption that all the alleles 

of all the donors are present in the defined DNA profile of the 

evidence 

•In practice generally only applied in case of (deduced) single 

source DNA profiles: random match probability and complete 

mixed DNA profiles of two contributors (some cases three 

contributors) 

•likelihood ratio method (preferably) or probability of 

inclusion/exclusion 

e.g. ‘the result of the DNA profile comparison is x times more 

likely if the prosecution hypothesis is true, than if the defence 

hypothesis is true’
18 May 2011 

2012: DNA match; no statistical interpretation 

D10S1248 vWA D16S539 D2S1338

Evidence 

Consensus 

Not in consensus 

(one observation) 

13 14 15 16 17 15 16 17 18 19 9 11 12 13 

10

17 19 23 24

25

Suspect 13 16 15 17 9 12 17 24 

• DNA profile suspect matches mixed defined (consensus) DNA profile of the evidence

• It is uncertain if all alleles of all donors are present in the defined mixed profile of the evidence
18 May 2011 

2012: Person of Interest can not be excluded 

D10S1248 vWA D16S539 D2S1338

Evidence 

Consensus 

Not in consensus 

(one observation)

13 14 15 16 17 15 16 17 18 19 9 10 11 12 13 17 19 23 24 25 

22 25

Suspect 15 17 18 19 10 12 22 24 

• DNA profile suspect does not match defined (consensus) mixed DNA profile of the evidence

• A relatively large number of alleles of the suspect occur in the defined (consensus) mixed DNA profile; 

 questionable allele is observed in High MW locus (D2S1338) that is prone to allele drop-out
18 May 2011 

Inconclusive DNA analysis result 

 • Result supports neither a hypothesis about the presence of the person’s DNA 

 in the evidence nor one about its absence 

 

 

 

 

 

Complex (LT) mixed DNA profile of a high, 

but unknown number of contributors 

DNA profile from highly degraded mixed DNA
18 May 2011 

Over the years: increase in the number of complex 

DNA profiles 

1. Increase in the number of case requests and samples 

2. Absolute and relative increase in the number of non-classical DNA 

traces (touch evidence). 

3. More requests for statistical evaluation of complex DNA profiles. 

• Low DNA concentration 

• NFI quantification method: Alu Quant real time PCR method 

• Enhanced number of PCR cycles or enhanced detection (i.e. 9 kV 

CE injection) 

• Three PCR replications (maximum volume as input for DNA 

analysis) 
18 May 2011 

Match/non match with a complex forensic DNA profile 

To report that two patterns match, without providing any 

scientifically valid estimate of the frequency with which such 

matches might occur by chance, is meaningless. 

DNA “inclusions” cannot be interpreted by the CJS without 

statistical evaluation of the evidential value. 

NATIONAL RESEARCH COUNCIL, DNA TECHNOLOGY IN FORENSIC SCIENCE 74-75 (1992). 

It is also bad science to discard DNA profiling data and to 

believe that this is always the conservative approach as this is 

only true if the complex DNA profile does not show 

exclusionary information.
18 May 2011 

The statistical evaluation of complex mixed DNA profiles 

is a hot topic in court
18 May 2011 

The statistical evaluation of complex mixed DNA profiles 

is a also hot topic in forensic science
18 May 2011 

The statistical evaluation of complex mixed DNA profiles 

is a also hot topic in forensic science

• Binary method (treats alleles as present or absent) 

• Semi continuous methods treats alleles as present 

or absent but assigns a probability to the events of 

drop out and drop in. 

• Full continuous models deal with the probability of 

drop out and other stochastic effects based on the 

intensity of the alleles visualized at a locus. 
18 May 2011 

Implementing in forensic DNA analysis: 

diversion of models and methods 

If our condition were truly happy, we would not 

seek diversion from it in order to make ourselves 

happy.

Blaise Pascal 
18 May 2011 

In contrast with: standardization on an ESS forensic 

DNA profile 

The technology enables world wide comparison of DNA data 

and worldwide DNA database searches. 
18 May 2011 

• Validation of and experience with state of the art 

commercially available DNA analysis systems (NGM) 

• Large experience with the analysis of low level real 

casework samples 

• Experience with semi continuous statistical models (LRmix) 

NFI critical expertise 
18 May 2011 

ISO 17025 compliance for forensic methods in case work 

• Accepted by the scientific community 

• Known and published error rates 

• Validated under realistic case conditions 

• Proficiency tests 

The forensic challenge 
18 May 2011 

The NFI developed a simple semi continuous model
18 May 2011 

The NFI developed a binary (semi continuous) model

The NFI model 

• alleles are present or not 

• alleles of donors can dropout with probability D 

• alleles can drop-in 

• No use peak height information data 

• No modulation of allele stutter (standard stutter settings) 

• no DNA degradation 

• no kinship 

• We know this model has strengths (simple) and short 

comings (not all the available information is used), but it 

may be useful!
18 May 2011 
18 May 2011 

The NFI model: an example four PCR replicates 
18 May 2011 

The NFI (semi continuous) model

Effect of drop-out probability 

Effect of replicates 

A low template mixture can give the same amount of 

evidence as a high template mixture! 

MINDSWITCH for our RO’s
18 May 2011 

The mixed DNA profiles of interest 

Examining the performance of existing probabilistic models in 

terms of: 

1. the ability to discriminate between donors and non-donors 

2. the stability of output data across reasonable settings of, for 

example, probabilities of drop-out and drop-in (calibration of the 

probabilistic model). 

3. consideration of parameters such as reproducibility when 

replicates of the same mixture are analyzed. 

4. Finally practical aspects such as time of analysis and ease of use 

are considered. 
18 May 2011 

Webinar: the mixed DNA profiles of interest 

• “open source” DNA profiles that have been made available 

by Robin Cotton from Boston University 

• The mixtures include low-level contributors and two, threeand four-person contributors with differing ratios and allele 

sharing. Using the data from the mixed DNA-profiles we 

have investigated the performance of our model. 
18 May 2011 

Example 4 person mixture 

Four known donors: A, B, C and D (1.6:3:2:1) 

Total DNA input: 0,4 ng 

A 84 pg

B 158 pg

C 105 pg

D 53 pg
18 May 2011 

Identifiler DNA profiles of the BU samples 

A B C D

D8S1179 13,16 11,13 14,15 13,16

D21S11 29,32.2 27,32.2 30,32.2 28,28

D7S820 8,11 11,11 10,12 8,12

CSF1PO 11,12 10,11 10,11 12,12

D3S1358 15,16 14,16 14,18 16,16

TH01 6,9 6,9.3 7,7 7,9.3

D13S317 11,11 11,13 11,12 12,13

D16S539 11,12 11,13 10,13 12,13

D2S1338 19,24 17,25 22,25 23,25

D19S433 15,15 14,15 12,14 13,13

vWA 18,19 15,18 15,16 15,19

TPOX 8,11 8,11 8,8 11,11

D18S51 13,14 13,17 16,18 14,20

Amel XY XX XY XY

D5S818 10,12 12,12 12,12 11,13

FGA 20,20 25,26 23,23 20,28
18 May 2011 

Input format of data: Genemapper Table output 
18 May 2011 

The NFI model 

http://forensim.r-forge.r-project.org/misc/LRmix.pdf 
18 May 2011 

The NFI model 

Wrong number of actual contributors: two; not three 
18 May 2011 

The NFI model 
18 May 2011 

The NFI model 
18 May 2011 

The NFI model 
18 May 2011 

Identifiler DNA profiles of the BU samples 

A B C D

D8S1179

D21S11

D7S820

CSF1PO

D3S1358

TH01

D13S317

D16S539

D2S1338

D19S433

vWA

TPOX

D18S51

Amel

D5S818

FGA

Total	LR	 245000	 27	 112000	 0.44	

A 84 pg

B 158 pg

C 105 pg

D 53 pg
18 May 2011 

Scrutinise the model 

Model uses parameters: 

• Theta correction 

• Allele frequencies 

• Number of contributors 

• Drop-out probability (per donor) 

• Drop-in probability 

What happens if the estimates of the parameters are incorrect: 

ROBUSTNESS 
18 May 2011 

Wrong number of actual contributors: two; not three 

Donor 

Non Donor 

Wrong number of drop out probability 

Wrong number of contributors and wrong drop out rate 
18 May 2011 

Scrutinise the model 

The performance of the probabilistic model is examined in 

terms of: 

1. the ability to discriminate between donors and non-donors 

2. the stability of output data across reasonable settings of, for 

example, probabilities of drop-out and drop-in (calibration of the 

probabilistic model). 

3. consideration of parameters such as reproducibility when 

replicates of the same mixture are analyzed. 

4. Finally practical aspects such as time of analysis and ease of use 

are important. 
18 May 2011 

ICFIS 2014 – Welcome to the Netherlands! 

9th International 

Conference on Forensic 

Inference and Statistics 

19-22 August, Leiden 

www.icfis.org