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TRANSCRIPT OF PROCEEDINGS

S CR 2014 0007

SUPREME COURT OF VICTORIA

CRIMINAL JURISDICTION

MELBOURNE

THURSDAY 20 APRIL 2017

(2nd day of hearing)

BEFORE THE HONOURABLE JUSTICE EMERTON

DIRECTOR OF PUBLIC PROSECUTIONS v. CLINTON JAMES TUITE

VICTORIAN GOVERNMENT REPORTING SERVICE7/436 Lonsdale Street, Melbourne Vic 3000 - Telephone 9603 9134161889

Pages 119 - 177

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DR ROGERS: Good morning, Your Honour.

HER HONOUR: Good morning.

DR ROGERS: Dr Duncan Taylor appears on the video-link and is

ready to give his evidence.

HER HONOUR: Good morning, Dr Taylor?---Good morning.

Yes, Dr Rogers. We have got to swear the witness in, I'm

sorry.

.DF:DM:CAT 20/04/17 SC 11A 119 DISCUSSIONTuite

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<DUNCAN ALEXANDER TAYLOR, sworn and examined:

DR ROGERS: Dr Taylor, do you have - did you prepare a

statement, a 19 page document dated 17 April 2015?---Yes,

I did.

Do you have a copy of that in front of you?---Yes.

And that's a truthful document?---Yes.

I tender that.

#EXHIBIT B - - Statement of Dr Duncan Taylor dated 17/4/2015.

Do you have another statement, 20 pages, dated 15 August 2016,

signed by you?---Yes.

And that's a truthful document?---Yes, it is.

Yes, I tender that.

HER HONOUR: What date did you give for that?

DR ROGERS: 15 August 2016.

HER HONOUR: All right. I have got here a statement dated 2

September 2016, is that not - that's the cover, is it?

DR ROGERS: Have I got the wrong date.

MR DESMOND: Yes, well, the cover page.

DR ROGERS: The cover page has got the notice of additional

evidence.

MR DESMOND: That's the 2nd of September - - -

HER HONOUR: It's the cover page that's the wrong date.

DR ROGERS: It's the date it was served, Your Honour, I

understand.

HER HONOUR: All right. Yes, I see this is dated 15 August.

#EXHIBIT C - - Statement of Dr Duncan Taylor dated 15/8/2016.

DR ROGERS: Yes, thank you.

HER HONOUR: Yes, Mr Desmond.

MR DESMOND: Thank you, Your Honour.

<CROSS-EXAMINED BY MR DESMOND:.DF:DM:CAT 20/04/17 SC 11A 120 TAYLOR XN XXNTuite

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Good morning, Dr Taylor?---Good morning.

Sir, were you provided with a copy of Professor Balding's

statement at some point?---No, I wasn't.

Okay. Is it correct - he's given some evidence that he did

have some conversations with you, as best I could

approximate it, it would be in the lead up to 22 June

2015 when he wrote his statement?---Yes, I think we did.

He asked you perhaps some questions in more detail about STRmix

and the program, those sorts of matters?---Yes, that's

right.

Did you happen to make notes of those conversations, by the

way?---No, I don't have any notes of those.

I just want to read to you, doctor, part of the professor's

report - this is on p.4. He says, "From Dr Taylor's

comments on p.1", so he's referring to your statement,

he's identified the statement of 1 July 2014, so it

appears he's referring to that. He goes on - - -

HER HONOUR: 3 July?

MR DESMOND: - - - and says, "It appears that this statement

has been prepared in response to a defence request for

further documentation about the workings and validation

of STRmix". He says, "I agree that such documentation

would be valuable". Firstly, do you agree with

that?---The documentation about the workings of STRmix

would be valuable?

Yes?---Yes.

He goes on to say, "And this statement goes some way" -

referring to your statement - "towards meeting this

request".

HER HONOUR: Can we just clarify, for Dr Taylor's benefit,

which statement we're talking about here, which of his

.DF:DM:CAT 20/04/17 SC 11A 121 TAYLOR XN XXNTuite

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statements? It seems to me it's the one dated 17 April

2015.

MR DESMOND: Well, I would have thought so, I couldn't find the

date that he refers to that, Your Honour.

HER HONOUR: Yes. So, Dr Taylor, it's your 2015 statement, the

one with all the algorithms in it.

MR DESMOND: Yes. Thank you, Your Honour, I missed the heading

to that paragraph. He identifies your second statement

of 17 April 2015?---Okay.

And goes on to say, "From Dr Taylor's comments on p.1 it

appears that this statement has been prepared in response

to a defence request for further documentation about the

workings and validation of STRmix. I agree that such

documentation would be valuable and this statement goes

some way towards meeting this request. I found

Dr Taylor's discussion of the difficulty arising because

the STRmix algorithm is 'not entirely step-by-step' to be

confusing and unnecessary". Do you agree that quote of

yours in your statement about the difficulty arising

because of the STRmix algorithm is confusing and

unnecessary?---I wouldn't necessarily agree that my

statement is confusing and unnecessary.

Well, it's the particular subject matter within the statement,

it may incorporate other subjects matters but this

particular one is you express some difficulty arising

because of the STRmix algorithm and setting it out, the

maths step-by-step, did you not?---Yes, and the reason

for that was, as I understood what I was being asked to

provide, was some step-by-step manner by which a person

could take the input material, put them through a series

of equations and then end up with the answer that STRmix


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gives at the end. Now, you can't do that because of the

way that STRmix works.

I'm sorry, doctor.

HER HONOUR: Can I just stop you for a minute, Dr Taylor.

Could we turn the sound up a bit, please, Mr Hansen.

You might be better off - I know you probably hate using

them - - -

MR DESMOND: I am generally, Your Honour, but I then find that

I speak lower because it's very loud in my ear.

HER HONOUR: Thank you.

MR DESMOND: I'll see how we go?---Shall I repeat my last

statement?

HER HONOUR: Yes, please.

MR DESMOND: Yes?---So the - what I was being asked to do, as I

understood it, when I wrote this report was provide some

step-by-step mechanism by which a person could take the

input material that was being provided to STRmix, take it

through a series of equations and end up with the answer

at the end that STRmix gave and because of the way in

which STRmix works it's not possible to provide that

linear series of equations that lead from inputs to

answers; that's the difficulty that I refer to.

Balding goes on to say, "There is no difficulty in principle to

describe a stochastic algorithm and there would clearly

be no interest in describing the actual realised values

of every step of the algorithm". Do you agree with

that?---That seems fair enough.

He then says that, "Also on his statement" - referring to your

statement on p.2 - "However, I can provide the rules (or

more technically the models) that govern". And Balding

goes on to say, "Is not completely satisfactory". Do you


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agree that statement of yours is not completely

satisfactory?---Well, I think I would need a little bit

more context as to what he considers to be satisfactory

to answer that.

Well, he goes on to say, "Yes, the rules is what is requested

but the mathematical models underlying STRmix are

generally well described in the literature and, in my

view, are not only cause for concern. What is less well

documented is a high level technical description of the

algorithm. I believe that this is not being made

available because of commercial considerations but I do

not think this is satisfactory in the criminal legal

context". Do you agree with those propositions?---Well,

there's more to the points really what you've just said

there. I agree that these sorts of algorithms should be

available to the judiciary or to the scientific public.

I would disagree that we haven't given those, as far as

how STRmix works, because we've published extensively on

every aspect of the way that STRmix works, all the

models, all the maths and all the algorithms.

He goes on to say that, "While the published literature

relating to STRmix is impressively large and of high

quality, it is at different levels and in different

places published at different times with much repetition

and referring to different versions of the program". Do

you agree with that?---Yes.

He goes on to say, "Defence experts should have available a

single document explaining how the program works and the

changes over different versions as well as the results of

validation checks and which versions they relate it". Do

you agree with that?---Yes, that would be reasonable.


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Do you agree that's not been done at this point for whatever

reason?---Well, the most complete compilation of all the

STRmix algorithms that are kept all in one place and all

up-to-date with the latest version of STRmix was in the

in the STRmix user's manual. That also includes a series

of changes across versions numbers in the back of the

manual there and we have defence disclosure policies to

make that available to defence. And just further to what

you said regarding the validation reports, typically they

- I assume that they would be talking about validation

reports for each - for the specific laboratory that's

validated, STRmix, which it would be available from the

laboratory. If you're talking about developmental

validations, then that's also present in the STRmix

manual.

He says, this is Balding, "This documentation would be

substantial and difficult for any one expert to absorb

and critically appraise, however, if such a document were

available to the international community of experts,

there would be long-term advantages through additional

opportunities for scrutiny that might uncover areas for

improvement and give greater reassurance than is

currently possible". Do you agree with that, sir?---I'm

not sure whether I agree or disagree with that.

Certainly I agree with the sentiment that the more

information you provide to the scientific public, the

more you're going to advance the field. I would say that

we have made all that information available but, as

previously pointed out, it's in different publications

spanning time.

M'mm?---It's really - whether or not we provide that material


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all in one block in a STRmix manual is really a matter of

convenience rather than access.

Well, I understood you to be saying if - and if it's correct

that all the algorithms and developmental validations for

each version are contained within the manual, I

understood you to be saying the manual is available, in

effect, in a litigation sense to the defence and the

judiciary but it's not generally freely available. Have

I misunderstood that?---No, that's correct.

Now, apart from other things that have occurred since we last,

since I last had an opportunity to ask you questions,

SWGDAM, that's the Scientific Working Group on DNA

Analysis Methods, have published guidelines for the

validation of probabilistic genotyping systems?---Yes.

As I understand it, and just reading from the copy I've got

here, "Following the public comment period the ad hoc

working group forwarded the final guidelines to the

SWGDAM executive board and they were approved for posting

on the SWGDAM website on June 15 2015. That's correct,

as you - - -?---Okay.

And clearly, as disclosed by the question and the document

itself, it sets out a series of guidelines addressing the

validation of probabilistic genotyping systems in

general, one of which is STRmix?---Yes.

You've sought to comply or adhere to those guidelines as the

developer or co-developer of STRmix; is that

right?---Yes.

You jointly authored a paper that was published in Forensic

Science International Genetics, volume 23 2016 pp.226-239

entitled, "Developmental validation of STRmix expert


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software for the interpretation of forensic DNA

profiles", agreed?---Yes.

Just quickly going to the abstract, it reads, "In 2015 the

scientific working group on DNA analysis methods

published the SWGDAM guidelines for the validation of

probabilistic genotype systems. STRmix is a

probabilistic genotyping software that employs a

continuous model of DNA profile interpretation. This

paper describes the developmental validation activities

of STRmix following the SWGDAM guidelines." That sounds

accurate, as I've read that part of the abstract to

you?---That seems correct.

Okay. Now, in the body of the article you go on to - the

precursor had been the description as to how the science

had developed, manual techniques for DNA profile

interpretation puristically based, et cetera, and you,

the authors, then get to identifying again the 2015

guidelines and you go on to say, could I suggest, "The

developmental validation of STRmix was initially

undertaken in 2012 following the requirements outlined

within the FBI quality assurance standards by analysts at

Forensic Science South Australia and the Institute of

Environmental Science and Research Limited, ie, ESR,

agreed?---Yes.

In paragraph 1.1 of the article you identified guideline 3.1 of

the 2015 SWGDAM guidelines being publication of

underlying scientific principles, agreed?---Okay.

And the paragraph commences, "All significant portions of the

statistical algorithms and underlying scientific

principles behind STRmix have been published in peer

reviewed scientific literature. Within table one we


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provide a summary of these models and algorithms and

their references aligned with the software version in

which they were introduced". Okay?---Okay, yes.

Now, when one then goes to table one, it's identified as a,

"Summary of the scientific principles the STRmix version

in which they were introduced and their publications".

The next line is, "Algorithms scientific principles and

methods", the first one of which is - it's listed in the

table is allele and stutter peak height variability as

separate constants within the MCMC"?---Okay.

Before I go through each of them as necessary, are you able to

answer - I assume you haven't got access to the document

where you are at the moment - if you have, you're welcome

to open it up?---No, I don't have it.

Are we talking about mass parameters within this table?---Okay.

The first one that I have just read out, "allele and stutter

peak variability is separate constants within the MCMC",

the heading under the column "version introduced" is

version 2.0; that's accurate?---I assume so, yes, yeah.

Does that mean for earlier versions there was no algorithm or a

different algorithm for modelling allele and stutter peak

height variability as separate constants within the

MCMC?---Could you just repeat that, sorry?

Okay. Perhaps you could explain what is meant by the phrase

"separate constants within the MCMC"?---For the allele

and stutter peak height variability?

Yes, yes, what's a separate constant mean?---Sure.

Is it a constant at each marker or- - -?---So within the DNA

profile that we're analysing, some of the fluorescence

that we're seeing, some of the peaks is going to be due

to alleles. If I use that term, you familiar with what I


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mean?

Yes?---And some of the fluorescence is going to be due to

stutters from those alleles.

Yes?---In early versions of STRmix we modelled the peak height

variability of stutters and alleles with one over-arching

model and then in later versions we refined the model we

used so that it still uses the same algorithm but

stutters and alleles had different constants within that

algorithm which means stutters - the peak high

variability of stutter peaks were tolerated less than the

peak high variability in allelic peaks in later versions.

Okay. But the change in version two, you may be able to tell

us approximately when version two commenced operations or

you may not, was done to improve the ultimate outcome of

STRmix, that is the production of the LRs?---Yes, and so

it is for a number of algorithms and ongoing efforts, we

continually refine and improvement the algorithms within

the program.

I understand. But you might recall the case of Tuite involves

the use of STRmix version prior to version two, it's

version one point zero something?---Yes, that's right.

The next category is peak height variability as random

variables within the MCMC. That was introduced,

according to the table, in version 2.3. Firstly, peak

height variability, is that a reference to both stutter,

alleles, spikes, blobs and any other artefacts or is it

only a reference to stutter and allelic peaks?---It's

only in reference to stutter and allelic peaks because

all those other artifactual peaks that you just

mentioned, it's presumed that an analyst has screened

those out prior to using STRmix.


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Okay. But where in the first category, allele and stutter peak

height variability are separate constants, which you have

explained came in with version two, peak height

variability is random variables within the MCMC, what is

that, how is that different from the first

category?---Sure. So within this new change that you're

talking about that came in with version 2.3 we actually

allowed STRmix to change how tolerant it was to peak

height imbalances for both stutters and alleles so that

if profiles were being produced in a lab that happened to

be slightly more variable than average DNA profiles, then

STRmix could adjust for that. Similarly, if they were

slightly less variable in peak height than the average,

then STRmix could adjust for that. Prior to that version

there was just one fixed value for the tolerance of peak

height variability for stutters and alleles that couldn't

shift.

So we could change variability there for the imbalance issue of

peak heights looking at, across an entire profile, that's

looking at the balance and whether it confirms?---No.

With this one you're still talking about within a locus,

you're still talking about individual peak height

variabilities, you're just talking about the ability of

STRmix to adjust to the variability that's been seen.

Okay. So it's restrictive to locus or does it include genotype

as well across the profile?---It's for all peaks in the

whole profile.

Okay. Well, does have to - does it either have to discriminate

and/or is it able to discriminate with, between allele

imbalance and genotype imbalance?---Well, there is no

real - - -


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Is that unnecessary- - -?---I'm not quite sure - - -

- - - that sort of distinction, genotype imbalance across a

profile, genotype - - -?---So allelic - there is no real

term "genotype imbalance" as far as I'm aware. Allelic

imbalance, I suppose, would cover that.

Would cater for it. Okay. The third category is model for

calibrating laboratory peak height variability. That's

said to have been introduced in version 2.0. Now,

firstly, is that model for it to be used, that requires

input of the individual laboratory validation data as

they have modelled peak heights in the past or is it

talking about something else?---That's talking about the

process of labs taking some validation data and using

this component of STRmix to calibrate STRmix for how that

ladder is performing.

I didn't ask you, so I will just re-trace, for that second

category, peak height variability as random variables

within the MCMC, did it do it, and, if so, what model,

how did it do it prior to version 2.3?---No, 2.3 we

introduced that feature of the model where STRmix could

adjust for the profile it was seeing with regards to peak

height variability. Prior to that STRmix couldn't adjust

to the individual profiles peak height variability, it

used a - like an average value from the laboratory

calibration data.

Okay. Well, that may then answer the next question. For the

third category of model for calibrating laboratory peak

height variability which came in with version 2, was that

addressed prior to version 2?---Yes, it was.

Application of - it says "Gaussian" G-a-u-s-s-i-a-n "random

walk to the MCMC process came in in version 2.3". What


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is the Gaussian random walk to the MCMC process in

layman's language?---In layman's language will be a

challenge but I'll see how I go. When you are trying to

describe a DNA profile or when STRmix is trying to

describe a DNA profile it will choose values for the

different mass parameters so it will choose a DNA amount

for each contributor and that would make a difference as

to how high it's expecting to see peaks. It will choose

values for degradation for each contributor and that will

dictate how much the peak highest is expecting to drop

off as the profile goes from left to right, and similar

for other mass parameters in order to build up an

expected profile but what it's expecting to see. Now,

how closely that expected profile aligns with the profile

you have observed sort of dictates how well those mass

parameters are describing what you've got. With each

iteration in the MCMC, so each new round of estimating

new values for these mass parameters, STRmix will take a

small step away from the current value that it's sitting

on and that small step away is called a Gaussian random

walk because the size of the step depends on a Gaussian

curve.

The application of that Gaussian step, was that catered for in

versions prior to version 2.3?---Prior to 2.3 we didn't

use a Gaussian random walk, we used a different method of

proposing these new mass parameters.

What was the method used in the version which I think is 1.08

but you might be able to correct me in the Tuite

case?---That method was a clipping and sliding method.

Sorry, clipping and what?---And sliding, which is to say we

have a small window from which those values could be


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chosen, that window would be sitting around the current

value and that window could slide up or down as the

analysis proceeded.

That clipping and sliding method, is that identifying a

particular algorithm or a mathematical equation?---A

particular algorithm.

Can you identify where, either what the algorithm is or where I

would find it?---That algorithm would be present in the

STRmix manuals that related to STRmix prior to version

2.3.

Okay. The next category is "modelling of back stutter by

regressing stutter ratio against allelic designation

which was introduced in version 2". Firstly, can you

just explain what's that identifying? I know what "back

stutter" is, but what's "back stutter by regressing

stutter ratio" as opposed to just looking at the stutter

ratio?---Well, what that means is that within a locus you

can create the equation of a line that lets you convert

an allele to a stutter ratio. So that's what we used.

Was modelling of back stutter by regressing stutter ratio

against allelic designation catered for in versions prior

to version 2?---Yes.

With a different algorithm?---No, with that same algorithm,

with a regressive, but with a regression algorithm.

What's the distinction, what's being identified that was

introduced in version 2 that apparently wasn't in the

earlier versions?---Well, I believe, from memory, in that

table that earliest version number we used is version 2

because that was the first commercially released version

of STRmix, so that's as low down as we go but a lot of

these things were present in prior versions because


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they're fundamentals to the working of STRmix.

Well, the document certainly doesn't say this and this is

published in the Forensic Science International, you

know, peer review - it's peer reviewed literature,

agreed?---Correct.

As I understand it, the STRmix program, correct me if I am

wrong, but was actually sold to FSL or did they just get

it for free, it was a commercial product when it was sold

to FSL Victoria?---So all the Australian labs received

pre commercial versions of STRmix for free. The first

commercial version was version 2, which is what we've

published on because that's the version that's available

to the international community.

Well, this particular category, that was in the earlier - well

- and specifically was in the Tuite version?---Yes.

Next category, "Modelling of back stutter by regressing stutter

ratio against LUS" - Professor Balding explained LUS

yesterday, it's longest- - -?---Uninterrupted sequence.

Uninterrupted sequence, thank you. And according to the table

introduced in version 2.3?---Yes.

So I'm assuming that because it's first introduced in 2.3, it

wasn't in the first commercial program, version 2, and,

therefore, wasn't in the non-commercial programs prior to

version 2, is that correct?---Correct, yes.

That modelling - firstly, perhaps, what's distinction here for

the modelling of back stutter by regressing stutter ratio

against LUS as opposed to the previous description of

regressive stutter ratio against allelic

designation?---Well, in the previous model where you

regress it against allelic designation, for each locus

you get an equation of a line, as I said, which lets you


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take an allelic value and compare that to the equation of

the line and get an expected stutter ratio come out of

that. What we found was that there was a model that

better described stutter ratio than simply this one

equation of the line, in particular some loci where the

stutter or with a repeat region wasn't a simple sequence

of repeats but was broken up by non-repeating regions, we

found this longest uninterrupted sequence was a better

description of the expected stutter ratio, so we refined

the model to use that longest uninterrupted sequence

rather than the allelic designation.

By what measure is it better?---Well, you can - - -

If you used a percentage term, if that was appropriate, is it

10 per cent better than the previous - - -?---Um, so what

you can do is graph allelic designation versus the

observed stutter ratio and you can fit an equation of the

line and you can get value, called an R-square value that

tells you how well that line describes the data, and I'm

relying on my memory a bit here but I believe that that

R-square value was around about 0.34, 34 per cent of the

variability was described by allele.

Okay?---We then did the same thing graphing longest

uninterrupted sequence against the observed stutter ratio

and that R-square value, from memory, was around 60 to 70

per cent, so it was - - -

So perhaps twice as effective?---You can't - it's not quite as

simple as that but it was more effective.

Okay. The next category is, "Modelling of forward stutter" -

forward stutter, is that restricted to, is it two base

points along the profile or four base points?---That's

one repeat units - - -


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One repeat unit?---- - - up from the allele rather than being

the standard stutter we have been talking about is one

repeat unit less than the allele, this is one repeat unit

more than the allele.

But if you were reading one repeat forward or back, is it plus

or minus 2BP or not?---It depends on the repeat in the

region that you're looking, so if it was a four base P

repeat it's plus or minus 4, if it's a five base P repeat

it's minus five.

Okay. While the modelling of forward stutter was first

introduced in the version 2.4, so do you accept by

inference it wasn't being modelled prior to version 2.4

in either commercial or non-commercial

programs?---Correct.

Next is, "Modelling of allelic drop-in using a simple

expediential or uniform distribution said to be

introduced in version 2.0", so allowing for your

explanation which you previously gave, was that modelled

in the Tuite STRmix version?---Yes.

Got the same algorithm as has been described- - -?---Yes.

- - - coming in with the first commercial one?---Yes.

Next is, "Modelling of allelic drop-in using a gamma

distribution" which is first introduced in version 2.3,

so applying the same logic it wouldn't have been

introduced in the non-commercial version,

agreed?---Agreed.

What's the distinction between the gamma distribution that's

measuring modelling allelic drop-in as opposed to using

the simple or uniform distribution? What are you

achieving by the different modelling with gamma?---The

gamma distribution came from a publication by a guy named


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Roberto Bucholz. He came up with a very neat way of

using a gamma distribution to model all the expected

drop-in that you see in a laboratory and when we saw that

we quite liked the way that that algorithm worked and so

we incorporated it into the next version of STRmix.

But am I current in understanding when you say you used the

phrase "we liked", what you mean by that it was a

superior model to what we were previously doing by

modelling with the simple or uniform expediential

distribution?---Yes, it provided a better estimate in

more situations.

Okay. Modelling - the next one is "modelling of degradation

and dropout". It identifies version 2. So are you able

to say that there was modelling of degradation and

dropout in the Tuite version?---There was.

Same - is that one algorithm, modelling of degradation and

dropout or is that two?---That's two separate algorithms.

Okay. Same algorithms for each in the Tuite version as is

identified in version 2 in table 1 of this

document?---Yes.

Next is, "Modelling of uncertainties in the allele frequencies

using the HPD". Just define what the HPD is for me,

please?---HPD stands for highest posterior density and

it's basically just a fancy name to take into account our

uncertainty in the True Allele frequencies in a

population because we're basing them on a small sub-set

we've used to create a database.

And that identifies version 2, so I'm assuming that that was

being modelled in the Tuite version, is that

right?---Yes, that's correct.

Same algorithm?---Yes.


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Next, "Modelling of the uncertainties in the MCMC". To the

layman that reads very vague, it's probably more specific

modelling of the uncertainties in MCMC. To you what does

that mean?---That means that each time you run an MCMC

analysis you get a slightly different answer. You expect

a certain amount of variability purely from that

stochastic MCMC process so in the later versions of

STRmix we were able to encapsulate that expected level of

uncertainty on an analysis by analysis case and include

that in the HPD estimate.

I'm sorry, does that mean if you did the run again or the

modelling again using STRmix you should get the same

result because you're allowing for the random uncertainty

using MCMC?---What it means is - well, for each analysis

that you run you get a point estimate and you get this

lower bound interval that we're reporting.

Yes?---If you were to run that analysis multiple times then 99

per cent of the time the point estimates will appear

above or the intervals, if you do cross comparisons

between the different runs.

Okay. That came in with version 2.3 according to table

1?---Yes.

So that wasn't being modelled in the earlier versions,

agreed?---Agreed.

Next is, "Database searching of mixed DNA profiles", it relates

to version 2, so I'm assuming that was being modelled in

the Tuite version?---Yes.

But what does that mean "database searching of mixed profiles"?

For what aspect? Because, I mean, you would, for a

particular analysis the crime scene stain profile would

be put in and perhaps the known reference sample of a


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victim and for the purpose of the likelihood ratio the

person of interest, in that sense there's no database to

search, so what is that identifying there?---Well, prior

to STRmix the standard way of dealing with perhaps no

suspect cases would be that you would test an exhibit and

attempt to interpret a single component from one person,

load that to a database in the hopes that it might match

someone and identify a potential offender. That process

relied on being able to interpret a single component from

a mixture. With the use of STRmix we were able to search

unresolvable mixtures against the database and identify

potential contributors to that mixture. So it just

opened up a lot more profiles to the stutter base

searching function mainly for no suspect cases.

I'm just making sure I've got this - as I read it, that came

in, there's just such a gap between the description and

then the version, I've got to make sure I get the - I

think that came in with version 2, so that was in the

Tuite version?---Yes.

And you understand this is a cold hit match case?---Yes.

So that particular modelling figured prominently in the Tuite

case or not?---Well, I don't know how the cold hit came

to be made.

Okay?---It may have been using standard - - -

HER HONOUR: Is this a modelling issue or just a feature of the

system?

MR DESMOND: I think it's a good question?---Well, it's just a

feature of the system.

HER HONOUR: That's right?---If you accept the fact that there

is a way that we can calculate a likelihood ratio if you

supply a reference, really this just a feature which says


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if you now supply a thousand references you can get a

thousand likelihood ratios all at once and look for

potential contributors.

MR DESMOND: Okay. I'll skip "familial searching" and move on

to - well, the next one is relatives as alternative

contributors, I'll skip that. The third last one is,

"Modelling expected stutter peak heights in saturated

data" and I raise this because it's a - there's a

particular aspect that Professor Chakraborty raises

concerning one item. That came in in version 2.3, so you

accept that modelling wasn't done prior to version

2.3?---That's right.

And you best explain what it actually means?---Certainly. When

you generate a DNA profile you will get alleles and

you'll get much smaller peaks which we have been talking

about called stutter peaks.

Yes?---As more DNA is used in the magnification reaction those

peak heights are going to increase and it happens at

roughly linear rate to a certain point and that point

would be when the instrument is no longer capable of

detecting any more fluorescence than what it's already

detected and that's called the saturation level.

Yes?---So above that particular level you can't really use the

observed peak heights of the allele to obtain the

expected peak heights of the stutters in that case

because they're saturated and the allelic peak heights

aren't representative any more of how much DNA is in the

DNA extract of that person.

M'mm?---So instead of using the observed peak height, which is

saturated, to come up with the expected stutter peak

height, we use the expected parent peak height that is


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within STRmix to come up with the expected stutter peak

height.

HER HONOUR: Why would - - -?---And it gets around that

saturation - - -

- - - saturate?---What was that, sorry?

Why would you saturate? Can't you control the amount of

phosphorescence or whatever it is that you're

measuring?---You can do and typically the laboratories

will have a certain DNA amount which is commonly called

the optimal DNA amount which just basically means they're

peaks most of the time will be relatively strong but not

so strong that they get into that saturation zone but

there are certain situations where just by random

sampling of the DNA extract you might sample more DNA

than what you're expecting and peaks will become

saturated or you may wish to push the amount of DNA that

you use in a PCR in order to try to obtain more

information about minor components which can drive the

major components more towards saturation. In that

situation, it's sort of a balancing point between getting

more information from the minor components and losing

information in the major component due to saturation.

Thank you.

MR DESMOND: Have you got Chakraborty's report handy? As I

understand it, you were given a copy of it because you

sort of responded to issues that he raised?---Yes, I do.

If you could go to p.6, doctor, please?---Yes.

The third bullet point he says, "The concept of expected peak

height and variances in observed stochastic effects in

LTDA are learned through execution of MCMC algorithms of

the model maker component of the software which uses


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genotype data from multiple single source samples (90

recommended for the version 108 version) with a range of

various template amounts. A user specified parameter

'saturation cap' defines the upper limit allowable for a

valuation of expected peak heights while comparing the

observed data. The choice of such saturation caps in

evaluating expected peak heights critically affects the

ratio of variance and expected peak heights

(overestimates the ratio) in case work use of stochastic

effects. During the review apparently it was noted that

in the R v. Tuite case at least one case example was

analysed in the STRmix by using a considerably larger

saturation cap of 32,000 RFU making the ratio of variance

over expected peak heights much tighter". Now, firstly,

is that issue, which I know you disagree with, and I'll

take you to your response in a minute, is that addressing

at all this particular modelling, that is the modelling

expected stutter peak heights in saturated data?---Yes,

that's referring to that saturation issue.

Okay. Do you agree he's at least correct in identifying that

there was one case work sample analysed by STRmix in this

Tuite case that used what he describes as a considerably

larger saturation cap of 32,000 RFUs?---I don't disagree,

I don't have any information to the contrary.

Okay. Are you able to tell us, from your clearly informed

knowledge of the program, what the general saturation cap

or the recommended saturation cap is or do you not make

any recommendation?---What we recommend is that each lab

develops a saturation cap that is calibrated to their

particular instruments. There's generally two different

levels of saturation cap that we find that laboratories


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come to. One would be around about 7 or 8 thousand RFUs,

that's for data that's produced on a particular model of

instrument known as a 31/30 or 31 hundred Capillary

Electrophoresis instrument.

Yes?---In the past few years there's been a new model of that

instrument, a new model of the hardware, which are called

35 hundred instruments. They use a different scale of

fluorescence so typically saturation caps for those

instruments tend to be around the 30,000 mark.

I'm looking for it but I don't know that if I can find it. The

settings used in calculation are generally set out within

the output data, aren't they?---Yes, that should have

saturation cap listed there.

To give you an example, I'm looking at F190 - it's a page

number of the case file in Tuite - if I can pick it up,

I'll tell you what item that relates to. I think it

relates to item 1-2. But in the heading, "Settings used

in calculation" - they go down the various parameters and

the saturation cap, I assume it is, but it just says

"saturation" is listed as 8,000 which would accord with

the 7-8 thousand range you identified a minute ago for

the 31/10, I think you said, or a 31/50 machine?---Yes.

To give you an example of the 32,000 at p.F212 of the case

file, which seems to relate to item 1-3, again going to

the page with, "Settings used in calculation" we go down

to the stutter cap and it's recorded 32,000?---The

saturation.

That's what it says under saturation - the word "saturation"

says 32,000?---Yes.

It doesn't say RFU but we're clearly talking about RFUs?---Yes.

So without trying to address the specific item issue, do you


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agree with Chakraborty or take issue with the balance of

his sentence there, "making the ratio of variance over

expected peak heights much tighter"?---No, that's not

necessarily correct.

Well, is it possibly correct as opposed to necessarily

correct?---It's not necessarily correct, it's not

necessarily incorrect. It would depend on - he is

talking about the ratio of variance over expected peak

heights, so when you go a 35 hundred that expected peak

height, because you've got a larger saturation cap, is

going to increase, so the bottom - - -

The variance is going to increase?---The expected peak height

is going to increase because you've got a larger

saturation cap, so he's talking about - - -

Sorry, are we looking at the difference between two peaks and

trying to determine does it fall within the stutter

range?---No, we're not talking about stutter at all here.

Okay?---We're just talking about saturation, okay.

Yes?---We're talking about the ratio, if we're using

Chakraborty's words, the ratio of variance over expected

peak heights at the very last - - -

Well, your modelling in table 1 as it's described is modelling

expected stutter peak heights in saturation data?---Yes,

but are we talking about my point in the table or are you

talking about Chakraborty's point?

Well, I asked you is Chakraborty's point relevant to this issue

in the table "modelling expected stutter peak heights"

and you said it's relevant, that doesn't necessarily mean

it's only addressing stutter peak - I'm not trying to

trick you up here?---Yeah.

Perhaps you just explain what you believe Chakraborty's


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addressing there?---So what Chakraborty is addressing

there is the ratio of the variance over the expected peak

heights. Now, sometimes that's going to be the expected

stutter peak heights, which is what that table was

talking about, or sometimes it's going to be the expected

parent - allelic peak heights.

Yes?---He says that the ratio is going to be much tighter and

he says that because when you increase your saturation

cap your expected peak heights are going to be larger, so

the bottle part of that ratio is going to get bigger and

that's what he describes as "getting tighter" but the

other point he hasn't addressed is the fact that the top

value on that line, so the variance when you're using

these larger saturation cap instruments, is also going to

increase, so the ratio may not change at all.

Well, I suppose it depends on the given situation, it may or it

may not change?---That's right.

Okay. But are you able to say whether - and I expect you won't

be because you're not, without being critical, hands on

in terms of the Tuite case with the items?---(No audible

response).

Whether it's that item that he's identifying there with the

larger saturation cap was seemingly done because the 35

hundred machine was now being used as opposed to the

31/50 machine?---I can't say with certainly but all I can

say is you wouldn't increase the saturation cap to 32,000

if you used a 31/30 instrument. It would have to be a

change of model or instrument.

That would be a significant error if that was done?---That

would be an error if that had occurred, yeah.

Okay. The second last item in table 1 is taking into account


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the factor of two, which is a quote, the factor of two,

and I have read about that somewhere but I can't

remember what it means, in LR calculations which is

introduced in version 2.3 and applying the same logic

wasn't being taken into account in earlier versions.

What is the - firstly, what is the factor of two in LR

calculations?---That is to do with likelihood ratio

calculations and it's to do with the way that you set up

hypotheses so if you don't use this factor of two or this

- it's called "factor of N" in the scientific literature.

Yes?---Then really you're talking about a particular component

of a mixture. If you do use the factor of N, you're

talking about the mixture as a whole.

In the Tuite case, likelihood ratios were calculated based on a

Crown hypothesis and competing defence hypothesis?---Yes.

But not with taking into account the factor of two in the LR

calculation as is necessary and recommended in versions

2.3 onwards?---Correct.

So what's not been addressed in the LR calculations, say, in

earlier versions that's now being addressed because they

both, on either, earlier and later versions, they both

would have a Crown hypothesis and a defence

hypothesis?---Perhaps I can explain by way of an example.

You could imagine you'd have a two person mixture where

you've got one major component that matches a person of

interest and you've got one minor component that's

different. Earlier versions of STRmix would give you the

likelihood ratio considering that the person of interest

is the major component and unknown is the minor component

compared to two unknown people being the source of DNA.

Yes?---Now, what STRmix version 2.3 and onwards does is


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compares the person of interest to the major component

and so you have the hypothesis that they're the major

contributor and there's an unknown minor.

Yes?---But you also consider them as the minor contributor with

an unknown major, so you're comparing it to both

components of the mixture and reporting like an average

of all of those comparisons, whereas in the prior

versions of STRmix you're just comparing it to the major

component in my example.

But it would also discriminate between the two?---What do you

mean by that?

Well, when it - you say it caters for determining when the

person of interest is the major contributor, it will come

up with a likelihood ratio?---Yes.

But it also looks at where he's possibly the minor

contributor?---Yes.

It just - it doesn't come up with just one figure?---Well, in

both versions of STRmix the references would be compared

to all components of the mixture but in the versions

prior to STRmix 2.3 it would give you the likelihood

ratio of for, say, the comparison to the major component.

Yes?---Only.

Yes?---Whereas later on in versions of STRmix where we

introduce this factor of two, it reports like an average

across all the different comparisons to all the

components of the mixture.

In the real life situation, assume the person of interest was

the actual contributor of the major component?---Okay.

STRmix would still give weightings, albeit I assume they would

be lesser in value, but would still give some weightings

to the person of interest possibly being the minor


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contributor?---It could do, yes.

When in this silly example I'm giving we would know that he's

just in fact not?---Say that again, sorry?

In this example that I'm giving, we would know in fact that

he's not the contributor of the minor sample, STRmix

potentially would still give some weighting to that

person of interest being the contributor of the minor

component to the mixed sample?---Well, as I said, it

could do, it depends if that amount of peak heights

variability was allowed so that if major peaks could pair

with minor peaks under the calibration settings produced

in the lab, then it would.

Yes?---If that level of imbalance is simply never seen in a

lab, then when it went to compare the person of interest

to the minor component the weights would be zero because

it would deem it impossible for him to be that minor.

Is that able to be done now with the items in the Tuite case,

that calculation?---Yes.

Is it your understanding - I know from what I have read about

STRmix and from what you've told us previously that if

defence makes requests for further calculations, then so

long as they're not silly requests and wasting

everybody's time, it would be expected that calculations

would be done?---Yes.

The last item in table 1 is, "Model for incorporating prior

beliefs in mixture proportions" and that was introduced

in the version 2.3, so a priori it wasn't introduced or

existent in earlier versions to 2.3, agreed?---Correct.

Does that have a scientific meaning? It sounds like a layman's

term, almost a religious term, "prior beliefs"?---What

that means is if you have some prior expectation on what


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the mixture proportions should be in a particular sample

and you analyse that sample with STRmix and the results

that STRmix give doesn't necessarily align with your

prior expectations, you can provide these, what we call

informed priors to, I guess, assist STRmix or provide it

some indication of your prior expectation.

Is that modelling both subjective and objective? It's

objective in terms of there's a known algorithm but it

requires some subjective input by the operator to the

particular prior belief that he or she believed is

relevant?---Yes, that's subjective component to that.

How does one have a prior belief about a crime scene stain and

its mixture proportions?---So the most common example or

scenario where this would be used is you may have a

profile where there appears to be peaks that are below

your analytical threshold, so peaks you haven't detected

and therefore peaks that are not going into STRmix to be

analysed.

Yes?---You might use those sub-threshold peaks to inform you

about how many contributors you believe there are to that

DNA profile but, of course, you're making that assumption

or you're making that decision based on information that

you're then not providing to STRmix, so there's a

disconnect between the information that you're using and

the information that STRmix is using.

Yes?---So then you can use these informed priors to tell

STRmix, "Look, I've said, for example, three

contributors, I believe one of these contributors is very

low-level, so I'll give a prior belief that one of the

contributors is at very low levels in this mixture

because I'm using this low-level sub-threshold


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information that you're not seeing", and then STRmix will

proceed with that.

Okay. That model or the algorithm that's the base for that

model, can you identify that at all in your statement -

which I have got to find where I put. It's the first of

the two today that you identified which sets out the

amount. The math really commences from about p.6, from

memory?---Yes. Well, it's not in that particular

statement because it's more of a user option rather than

a fundamental mathematical principle.

But it wasn't a user option for the Tuite case, in any

event?---Correct.

Can you tell me what the algorithm is or is it too long-winded

to regurgitate and you'd need it in front of you to see

it?---I can give hopefully a layman's explanation.

No, no the actual equation?---Well, the equation is the

equations for a normal distribution.

Okay?---You provide your prior beliefs and mixture proportions

by supplying means and variances of normal distributions

for what you believe the mixture proportions should be

and then STRmix using the densities of those normal

distributions in order to adjust the probabilities that

it obtains.

Okay. You go on in that article, "Developmental Validation of

STRmix" - "so STRmix uses the quantitative information

from an electropherogram, such as peak heights, to

calculate probability" et cetera. "The weights across

all combinations of that locus are normalised so they sum

to one". Do I understand another way or they sum to 100

per cent, the total weightings, which often we express in

percentage terms and see them in Deakin tables, they all


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seem to add up to 100 per cent, is that saying the same

thing?---Yes.

Okay. You then go on to say, "STRmix describes the

fluorescence observed in one or more EPGs using a number

of models that describe various properties of DNA profile

behaviour. These are described as mass parameters and

include a template for each contributor, a locus specific

amplification efficiency for each locus, a replication

efficiency for each PCR template and a degradation for

each contributor. This biological model is described in

Bright et al. reference 16." Reference 16 is Bright,

yourself Curran, Buckleton, developing allelic and

stutter peak height models for a continuous method of DNA

interpretation, FSI Genetics Volume 7 in 2013. So, I

then want to go to that paper. Firstly, I should ask

you, that sentence incorporates a number of propositions,

so I'll just quickly read them. "These are described as

mass parameters and include a template for each

contributor, a locus specific amplification efficiency

for each locus, a replication efficiency for each PCR

replicate and a degradation for each contributor. This

biological model is described in Bright et al." When I

was looking at this the other day, I'm reading that as

you relying upon this Bright reference as giving you the

biological model for degradation for each contributor.

Have I misunderstood that?---It's difficult for me to

comment without the paper in front of me. It could be

for the whole sentence.

Well, can we approach it this way, I'll now read you the

extract or the relevant parts of the - not the extract,

the abstract of reference 16 developing allelic and


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stutter peak height models, et cetera?---Okay.

"Traditional forensic DNA interpretation methods are restricted

as they are unable to deal completely with complex

low-level or mixed DNA profiles. This type of data has

become more prevalent as DNA typing technologies become

more sensitive. In addition, they do not make full use

of the information available in peak heights. Existing

methods of interpretation are often described as binary

which describes the fact that the probability of the

evidence is assigned as zero or one (hence binary). See

example one." New sentence, "These methods are being

replaced by more advanced interpretation methods such as

continuous models. In this paper we describe a series of

models that can be used to calculate expected values for

allele and stutter peak heights and their ratio SR. This

model could inform methods which implement a continuous

method for the interpretation of DNA profiling data".

You wouldn't take issue, I've read out accurately the

abstract?---I'm happy with that, yes.

In the body the article, "Continuous methods make assumptions

about the underlying behaviour of peak height or the

variability in the ratio of the two peaks of a

heterozygote and the ratio of an allelic peak height to

stutter peak height to evaluate the probability of a set

of peak heights. These models may be developed from

empirical data external to the profile under

interpretation, by a combination of external data and the

profile under consideration, or simply by the profile

under consideration. We would tend to favour the

combination approach". The combination approach is the


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combination of external data and the profile under

consideration. Now, I think I know but what is the

external data and is that combination approach- -

-?---That would be - - -

- - - which forms the basis for STRmix; is that right?---Yes.

So in that instance the external data would be the

calibration data that's been used in the validation of

STRmix for that particular laboratory and you use that

calibration data or that external data to inform some

parts of the workings of STRmix and the models within

STRmix and then, as you're analysing the profile itself,

that is informing STRmix of the values of certain mass

parameters and all of that combined ultimately leads to

your deconvolution or your likelihood ratio.

Well, the calibration data, does that include the internal data

from the particular laboratory that's used for variance

inputs?---Yes.

Do you agree, doctor - pardon me while I find it - there are a

number of unknowables in reality in relation to the

interpretation of DNA and the attempt to interpret it by

a DNA interpretation system such as STRmix?---Yes.

I want to list what I would suggest to you are the unknowables

and put it in this context that it's really these

unknowables which STRmix is attempting to model, in other

words, to fill in the blanks?---Okay.

The blanks in the sense of without the modelling they are

unknowable?---Okay.

The number of contributors to the profile, that's unknowable,

you never truly know the number of contributors to any

given profile, agreed?---Agreed.

The DNA amounts of each contributor?---Agreed.


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The degradation of each contributor?---Yes, agreed.

The amplification efficiently of each locus?---Yes.

The replicate amplification strength?---That's right.

And the level of peak height variability within the

sample?---That's right.

And at least those and they are probably a number of others, if

there are you may be able to tell the court what they are

now, that are being modelled discretely each of these

unknowns?---Yes. As you said before, this is what STRmix

is attempting to inform us on when it analyses a DNA

profile.

Now, within this article, "Developing allelic and stutter peak

height models" there are certainly sections which address

stutter, 3.3 is entitled, "Modelling peak heights", 3.4

is entitled, "Application of the model" that you have

identified in the article for mass and stutter. Then it

goes on to the discussion and the final acknowledgement

for the work, okay?---Okay.

Just one particular issue before I get on to what I'm

addressing. There's a sentence here, "Unexpectedly the

scatter plots" that you've identified in figure 8 in the

article, and there's figure 8A and figure 8B - so I'll

read out what they are - figure 8A log 0 to the H over

capital E to the H for the high molecular weight allele

versus log 0 to the little L, O to L over E to L for the

low molecular weight allele for each heterozygote locus

and B, diagram B, log O little a, I think it is, it's

hard to read, over E little a for the allelic peak versus

log OA negative 1 over E to the A negative 1 for stutter

peak but the sentence I'm asking you about is this,


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"Unexpectedly the scatter plots in figures 8A and B

indicate there is no detectible correlation between

stutter and allele in this biological model". When I

read it that sort of gave me some concerns but I'm

probably not understanding what you and the other authors

are describing there. Are you able to explain that

without the article in front of you or not?---I have to

try and cast my memory back as to what - all right, I

think, I know what we were talking about with that

particular sentence. Our thinking to that point was that

- well, stutter is a process that occurs during PCR so

within each cycle of the PCR the allele that we're

targeting is replicated over and over again in an

expediential fashion.

Sure?---At some point or in some of those amplifications there

will be a misalignment of the template strand and the

strand that's being made, so the copying stand, and

that's what leads to a stutter peak. The thinking is,

and it's still a reasonable theory, is that if that

stutter occurs very early on in the PCR process, what you

would expect to see is a smaller than expected allele

peak height and a larger than expected stutter peak

height because more of the fluorescence has gone into the

stutter rather than being part of the allele as it should

be. So what you would expect is that you - if that was

the case you would see that correlation as you would see

smaller allele - parent peak heights that were smaller

than expected correlating with stutter peak heights that

were larger than expected, however, we didn't see that in

the data that we looked at, which means one of two

things, either that correlation doesn't exist and we need


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to rethink the way that works, that model works, or that

the correlation does exist but it is too small to observe

in amongst the other noise present in the system.

The discussion then refers back to previous publications

suggested that LUS is a better explanatory variable for

SR than allele designation. What I'm putting to you is

this article is really addressing modelling in relation

to stutter ratio?---Yes.

So I go back to the sentence which included things other than

stutter ratio, "Mass parameters include a template for

each contributor, a locus specific amplification

efficiently for each locus" - that's not stutter, is it,

that's a different parameter?---No, that's different.

A replication efficiency for each PCR replicate, again, that's

not stutter, that's a different model?---Correct.

And a degradation for each contributor. Now, what I'm putting

to you, I was concentrating - I had in mind concentrating

on the degradation issue but I might address the others

as well, but at least as at this point in your validation

paper, you're referencing reference 16, "Developing

allelic and stutter peak height models" as a basis for

the modelling of the degradation for each contributor and

that article, I'm suggesting to you, does not identify a

model for degradation as it's not addressing degradation

or the rate of degradation; do you accept that?---Yes,

that sounds fair.

Okay. You then go on to say in the validation article,

"Drop-in is optionally modelled as a gamma distribution

following" - I'm not sure how you'd pronounce

this - Puch-Solis, I'm being told. "In addition STRmix

employs a per allele stutter model, the parameters of


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which are based on empirical data". One of the

references is the one I have just taken you to, what I

was calling your reference 16?---Yes.

And you also reference papers at 20 and 21, the first one being

by Messrs Brooks, Bright, Harbison and Buckleton

characterising stutter in forensic STR multiplexes and 21

is an article by Messrs Bright, Curran and Buckleton,

investigation into the performance of different models

for predicting stutter. I'm going to go to those

articles, Your Honour. I wouldn't mind a short

mid-morning break, if possible.

HER HONOUR: Yes. Is there any difficulty with the video-link

if we take a short break?

MR DESMOND: Keep to going as far as I'm concerned.

DR ROGERS: Yes, I think it would be more prudent to keep it

going rather than to stop it and start again.

HER HONOUR: All right. Dr Taylor, we are going to take a

10-minute break, because we will sit through until one

when the luncheon adjournment will take place?---Okay.

So I'm happy - we are going to keep the video-link running,

that doesn't mean you have to keep sitting there though.

My associate will be or Mr Hansen will be in touch about

resuming at 10 past 12?---Okay, thank you.

The court will resume sitting at 10 past 12.

<(THE WITNESS WITHDREW)

(Short adjournment.)

<DUNCAN ALEXANDER TAYLOR, recalled:

HER HONOUR: Mr Desmond.

MR DESMOND: Thank you, Your Honour. Just to give you the just

to give you the context, doctor, of where we were at, so

this validation article, the authors say, "Profile


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degradation is modelled as expediential" and you have got

references 17 and 18 there, 17 is Bright, Taylor and

Buckleton Degradation Forensic DNA Profiles Australian

Journal of Forensic Science Volume 45, 2013. 18 is

Buckleton Kelly Bright Taylor and that Tvederbrink and

Curren utilising allelic drop-out probabilities estimated

by logistical regression and case work, Forensic Science

International Volume 9 2014. So I will take you firstly

then to reference 17 degradation of Forensic DNA

Profiles. The abstract reading. "Selected profiles

typed at the Pro Mega Power Plex 21, PP21 loci

re-examined to determine if a linear or expediential

model best describe the relationship between peak height

and molecular weight. There were fewer large departures

from observed and expected peak heights using the

expediential model, the larger differences that were

observed were exclusively at the high molecular weight

loci. We conclude that the data supports the use of an

expediential curve to model peak heights versus molecular

weight in PP21 profiles, we believe this observation will

improve our ability to model expected peak heights for

use in DNA interpretation software". The article then

commences, I will read this part of it. "Typically the

samples will be amplified using commercially manufactured

STR multiplexes that analyse many loci simultaneously".

Can you just remind me, what is meant by

multiplexes?---That means a combination of a whole - a

combination of looking at many different regions of the

DNA all within the one reaction.

So looking at many - I just didn't hear the word?---Many

different regions of the DNA all within one PCR reaction.


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The sentence then continues, "With subsequent polymerase chain

reaction PCR product generated in a Capili

electrophoreses instrument. The resulting DNA profile is

an EPG, the heights or areas of the peaks within the area

EPG are approximately proportionate to the amount of

undegraded template DNA. However this relationship is

affected by a number of systematic factors". You accept

that?---Yes.

A bit further on there is a paragraph that commences, "The

modelling of expected peak heights is important in the

interpretation of forensic mixtures", that's obviously

true?---Yes.

You go on to say, the authors have previously described a

series of models that can be used to calculate expected

values for allele and stutter peak heights and their SR,

that is their ratio, known shortcomings of the binary

model have led to the development of new and improved

models that factor in the probability of drop-out.

Subsequently fully continuous interpretation models have

been developed. These models else take the quantitative

information from the EPG, for example, peak heights, and

use them to calculate the probability of the peak heights

given all the possible genotype combinations for the

individual contributors". That's sounds accurate?---Yes.

You go on then to say, "It is important to understand how

degradation affects these models. The simplest model is

linear. That is the expected peak height declines

constantly with respect to molecular weight. This can be

demonstrated crudely by taking a paper EPG and drawing a

downward sloping straight line across the apex of the

heterozygote peaks from to the lowest molecular weight


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locus to the highest molecular weight locus. A linear

model has previously been suggested by the current

authors". You go say, "In this work we investigate

linear and expediential equations for modelling

degradation within single source Pro Mega Power Plex 21

profiles". You agree that was the investigation, it was

for modelling degradation within single source Pro Mega

PP21 profiles?---Yes.

It is a relatively short article, without being critical. You

then describe the method, there are some algorithms and

then there is a brief paragraph, results and conclusions,

part of which reads. "We can see that more extreme

positive departures from expectation occur at the high

molecular weight end, in approximately 350 BP" - just

remind me again, what's that, base points?---Base pairs.

Base pairs, thanks. "Approximately 350 BP and above and

extreme negative departures occur in the mid-zone. This

is expected if we force a straight line on an

expediential curve". Can you just explain that firstly,

the reference to more extreme positive departures than

expected at the high molecular weight end and the extreme

negative departures in the mid-zone, what is that

identifying?---You can imagine if some data that you are

looking at has an expediential curve and if you were

describe an expediential curve you could imagine like a

ski slope that starts off very steep and then it flattens

out as it going along. So now imagine that you wanted to

try to describe that curvy ski scope with a straight

line, what you would do is you would you start at one end

and sort of draw a line as best you could through the

slope and what would you find is in that mid-section the


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bendy curve would be below the straight line and then as

you got to the end of the curve the bendy bit would be

above the straight line because the straight light

continued downwards into the ground, that's really what

that is talking about.

Thank you. And you go on to conclude, "We conclude this

evidence supports the use of an expediential curve to

model peak heights versus molecular weight in PP21

profiles." Am I correct in understanding that the

modelling of peak height versus molecular weight that's

addressing the degradation or the rate of

degradation?---Correct.

Do you agree this article does not address an investigation

into modelling degradation within complex mixtures

sourced from PP21 profiles?---Would I agree that it

doesn't address degradation?

Does not investigate. I will read out the investigation

sentence. "In this work we investigate linear and

expediential equations for modelling to generation within

single source Pro Mega Power Plex 21 profiles?---Yes,

that's right, so we used single source profiles to

generate our models.

Now the other reference was reference 18, just reminding you

again, one of the authors is yourself, titled "utilising

allelic drop-out probabilities estimated by logistic

regression in case work. Which is FSR Genetics Volume 9

2014 pp.9-11. I will read out part of the abstract.

"Some advanced methods for DNA interpretation require a

probability for the event of drop-out. Methods have been

suggested biased on logistic regression. Two of these

respectively use proxy for template et cetera, both of


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these methods allow different modelling constants from

each locus, a variant of the model using an expediential

curve is discussed, this variant constrains the constants

to be the same for every locus. We tested these two

methods and the variant by developing the constants

(training) on one set of data and testing them on

another. This mimics the likely use in case work. We

find that the new variant appears to be the most useful

in that it performs better than the other two options

when trained on one data set and used on another. The

hypothesised reason for this is that locus to locus

variation and the amplification efficiently varies with

time, multi-mix batch, or from sample to sample". So

that's the end of the extract. The reference to

multi-mix batch, I think I know what that means, perhaps

can you explain that?---I'm not exactly sure what that

refers to.

Then I withdraw my suggestion that I think I know what that

means. In any event, I'm addressing this degradation

issue and on p.2 of the document, "Experience in case

work has also suggested that there is a locus effect in

addition to a general downward slope", do you agree

that?---Yes.

"As an example, in one report 3 loci within the identifier,

that's the trademark, Multiplex, were preferentially

inhibited top varying extents in the presence of a

laboratory cleaning agent. Multi-mix is produced in

batches and it is conceivable that the locus balance in

one batch is different from another". Are you able on

the spot to say, well, yes, that's accurate, or do you

say, well, it must be because it is in it, but I really


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need to see the article because of the multi-mix and

batch reference?---I think I am happy to agree that's

accurate. I assume Multi-mix perhaps means a Multiplex

as I was speaking about before.

"Collectively these factors suggest that loci may be above or

bow the trend line", is that a reference to the

expediential curve or the straight line?---The

expediential curve.

"And whether a specific locus is above or below may change from

time to time or even sample to sample",

correct?---Correct.

"Models ignorant of such effects are likely to underperform";

correct?---Yes, by perform, they won't have as much

ability to distinguish contributors from non-contributors

so there would be lower discrimination power as a result.

Would you say that again, they won't be able to distinguish

between contributors and non-contributors?---And

non-contributors, there will be less discrimination power

in the system.

I am just trying to get my head around, if there is a

non-contributor there would be nothing to see?---When you

compare someone who is not a contributor to a profile you

expect a likelihood ratio that favours their exclusion.

I see what you mean?---That's what I mean.

The authors then say "there are currently two published

logistic regression drop-out models". I will not

describe them at present purposes. But you go on to say,

"However, the question presents do locus effects

developed for one set of training data translate to a

future set of data? This question is more than academic,

if multiplex batches or even samples differ in locus


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amplification efficiency then transport ability of the

model to future profiles may be an issue, accordingly it

may be advantageous to consider a model that incorporates

the concept of degradation but does not include a locus

effect", is that accurate?---Yes.

Do you say that the model that accounts for the rate of

degradation in the current version does or does not

include locus effect?---In all versions of STRmix we have

always had a locus effect as well as a degradation model.

Can you then explain the sentences I have just read out,

"Accordingly it may be advantageous to consider a model

that incorporates the concepts of degradation but does

not include a locus effect"?---So I think what that

sentence is saying is, a locus effect may be important or

it or may not be important and it is worth investigating

if those are the cases.

If I put to you what it is saying is, if Multiplex mixed

batches or even samples differ in locus amplification

efficiency then you can't transport the model to a future

profile and, therefore, the advantage would be we better

investigate to see the concept of degradation absent

locus effect because if we can do that that would be the

favoured route to take?---I can give you some sort of

theory here. What you are trying to do when you are

analysing a DNA profile or describing a DNA profile is to

do so with as few variables as possible because that's

going to be the most powerful system, so the offset, or

what is playing against that is the model has to

reasonably describe the DNA profile it is seeing, so if

you cut out too many variables it is just going to fail

to explain the profile you are seeing. So it is always


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favourable to have as few variables as possible, but you

have to obviously increase those until you get to the

point where you are explaining your profiles, so whilst

it might be in a general way it might be favourable to a

simpler system, it is to a point.

The results section of the paper say, "We use the mean log

(likelihood) per allele to score each of the models. The

model which yields the highest mean log (likelihood) is

regard as a preferred model. Therefore, if on average

one model yields higher log (likelihood) values than the

other models then we would regard this as evidence of

superior performance", and the results are given in what

are described as tables one and tables two. Do you agree

with that?---Yes.

"For the Power Plex 21 data T with a little 1 regularly gave

the highest mean (likelihood) in the training and test

sets, refers to table one, we interpret this as meaning

that pristine source data is too good to show the

expected degradation effect and, therefore, not suitable

to train these logistic models". Is that

accurate?---Yes.

Is that meaning degradation rates should not be calculated or

modelled based on samples taken from say scientists at

FSL as a data set, because they are pristine ones?---I

think what that this paper is talking about, when you are

talking about the logistic models in the paper talking

they are about a model for probability of drop-out, not

degradation necessarily. It is a drop-out probability.

That will shorten the exercise. I will just read the next

sentence. "However, we conclude that further development

is required in the application of locus specific effects


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and it is likely that these locus effects will vary from

profile to profile or time to time". Then there are the

acknowledgements. So I think from your previous answer

you are agreeing this paper is not an authority or a

reference paper for a model for the rate of

degradation?---It wouldn't be the main focus for the

paper, no, it is more of a drop-out focus.

I am just a bit concerned about the caveat, because the point

I'm trying to address is, in your validation paper to

accommodate the SWGDAM 2015 guidelines for probabilistic

genotyping you are quoting the profile degradation is

modelled as expediential and the references are those,

this one I have just taken you to, which I'm suggesting

is not an authority, doesn't provide a model for profile

degradation, nor indeed did the previous one which was

reference 17, which I have now got to find again, because

that only investigated single source PP21

profiles?---Well, the model we produced for degradation

from the single source samples is applied to mixtures.

Now, do you have any peer reviewed article supporting the

proposition that it is appropriate to apply the model

that you developed for the investigation into single

source PP21 profiles to complex mixtures that have been

amplified with PP21?---We have papers that look at the

application of some of the models within STRmix between

single source and mixed profiles and found that they are

applicable.

Can you identify for me now if possible the relevant papers or

alternatively will you undertake to identify those papers

in due course and provide them to the Crown so they can

be made available to the defence?---I can do that. One


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of the papers in particular is called something along the

lines of factors affecting peak height variability in STR

data, but I will have to track down.

Are you one of the joint authors of that?---Yes.

Factors affecting peak height variability in?---In STR data, I

think.

I understand. Returning then to the validation article. You

go to say, I think I read this out previously, "Drop in

is optionally modelled as gamma distribution following

Puch-Solis. In addition STRmix employs a per allele

stutter model, the parameters of which are based on

empirical data", and you reference for that sentence

articles, references 16, which is the one entitled

developing allelic stutter peak height models, 20 is the

Brooks Bright Harbison Buckleton characterising stutter

in forensic STR Multiplexes and the last one, which I

have just taken you to, investigation into the

performance of different models for predicting stutter.

I may not have just taken to you but I will take you to

that. So if we look then at the first reference, 16,

which is the developing allelic and peak height stutter

models for a continuous method of DNA interpretation. We

are looking for a stutter model, allele stutter modern,

the parameters of which are based on empirical

data?---Okay.

Within this article, I am obviously trying to avoid reading out

an entire article, but the first reference to a

definition for stutter ratio follows on from the

paragraph "loci where the alleles were repeated by one

repeat were disregarded because stutter is likely to

interfere with the allele height of the low molecular


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weight allele in an additive manner. These have

previously been referred to as a stutter affected

heterozygotes. In total 2,323 heterozygotes loci were

identified as being suitable for analysis. Stutter ratio

was defined as SR equals O little (a) minus 1 over O to

the (a) minus one refers to the observed height of the

stutter peak and O to lay of the parent peak". Now that

definition, that's not the model, is that right?---That's

just an equation for determining stutter ration.

I am trying to identify the model in this paper that was

sourced from empirical data. Are you able to describe

the model and I will search for it in the paper, or we

can - - - ?---At some point.

Under the paragraph 3.1 "stutter" you have got "the following

linear modern was proposed to describe the relationship

between SR and the explanatory variables LUS and locus

L"?---That's the model.

It then reads "SR to the little i equals Beta to the little O,

L plus Beta to the, looks like 1.1, or 1.L, LUS to the

little i and the sentence after is, "This was termed the

stutter model, linear modelling of stutter has been

reported previously" and then there are two references,

22 and 23. So that's the stutter model?---That's the

stutter model.

And do you rely upon where you said in the validation article

the parameters STRmix employs a per allele stutter model,

the parameters of which are based on empirical data. Do

you rely upon those references 22 and 23, I can read out

the titles to them if you want me to, in this paper as

authority for the proposition that stutter model is a per

allele stutter model placed on empirical data?---Yes,


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yes.

In short, if you can, can you explain, is that model

calculating a stutter ratio at each marker, at each peak

or at each genotype, what?---The model itself there has

parameters which are dependent upon the marker or upon

the locus and upon the longest uninterrupted sequence

within that locus that, around that longest uninterrupted

sequence is an allele specific property so that model is

locus specific, but it is also sourced allele specific

because locus uninterrupted sequences are allele

specific.

But does it in the end provide, and I am just pulling a figure

from mid-air at the moment, does it give you a figure per

locus that if, for example, there is a greater than 30

per cent ratio difference between what seems to be the

peak height and the sister peak, then that sister peak,

if it is greater than the 30 per cent is stutter, is that

what it is doing?---No, because all these results are

based on single source samples of known origin, we know

when the peak is a stutter or is an allele, this model

just provides the expected stutter ration for each allele

at each locus, it does not talk about peak height

variability of stutters.

But it is giving a per cent type figure at each locus that

STRmix uses in deciding whether, how much weight it gives

to a particular peak as being allelic or not?---Yes,

that's, it uses that information that is part of the

information that STRmix use in its assessment of the

profile.

Is that a constant, it would seem to me that must be a

constant, not a constant per marker, but if an analysis


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was done today by STRmix and an analysis was done in two

weeks' time by STRmix this appears to be a constant at a

given locus for any given profile analysis?---The

expected stutter ratio is a constant per locus and per

allele.

Where is that published, or is that information published as to

that the expected stutter - what's the phrase I'm looking

for, stutter ratio?---Expected stutter ratios.

Expected stutter ratio per locus, where would I find that, for

further reference?---That sort of information would be

present in individual labs' validation reports in

preparation for STRmix.

So that's an internal validation phrase in this case?---It is

not the sort of, yes, it is not the sort of information

that journals are interested in publishing.

Is that - you may have answered this I can't recall. Is that

novel or new with subsequent versions or that's always

been the case that it is a per locus stutter ratio that

is inputted?---There has always been a per locus stutter

ratio, but from version 2.3 onwards it was also

incorporating the longest uninterrupted sequence rather

than just an allelic designation so there was an

improvement in the model when we went to version 2.3.

Your next substantive paragraph in the validation article is

addressing guideline 3.2 of the SWGDAM guidelines,

sensitivity and specificity studies. You recall that

guideline 3.2?---Yes.

"With respect to interpretation methods sensitivity is defined

as the ability of the software to reliably resolve the

DNA profile of known contributors within a mixed DNA

profile for a range of starting DNA template", that's the


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objective?---Yes.

Within the paragraphs addressing this issue there is a

paragraph that commences with, "Sensitivity and

specificity studies, however, have a scientific component

to them and it may be desirable to use the best estimate

available for these. If these studies are used to

formulate decisions such as assigning terms to a verbal

scale then it should be noted that they refer to the

point estimate and not the lower bound. This has an

additional and possibly undesirable consequence that if

the verbal scale is calibrated from the sensitivity and

specificity plots and then this is a scale is applied to

the lower bound the scale itself now possesses an element

of conservativeness". Were you able to take that in and

explain to me what you are addressing there where you say

this has an additional and possibly undesirable

consequence?---Yes. When we are carrying out these

specificity and sensitivity tests it involves generating

a large number of likelihood ratios using STRmix for

contributors and for non-contributors and we have a look

at those likelihood ratios for DNA samples over a range

of input DNA amount. If you were to generate those

sensitivity and specificity plots, which sort of graft

these likelihood ratios over DNA amount, there are

different values you could choose to graft, one would be

the likelihood ratio point estimate, which is what we

have used in all of our studies, and another would be,

that lower bounds HPD interval that we spoke about just

before the break, so we always choose the point estimate

as the value to graph and what that sentence or couple of

sentences that you just read out is saying is that if you


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create the sensitivity plots using the point estimate and

then you use those sensitivity plots to come up with a

verbal scale that you are going to report in court as to

how much or what level of the support the results give to

particular inclusions or exclusion, but then you were to

actually report the lower bound likelihood ratio in your

case work it means you have generated your verbal

equivalent scale on the point estimates and then applying

it to the lower bound interval instead, so there is a

disconnect. It is basically a warning to say not to do

that.

Shortly after that paragraph that I read there is a paragraph

that commences "our preferred procedure when using STRmix

is that the analyst assesses whether a person of interest

is excluded prior to either their assessment of the

results of software calculations or interpretation of the

profile using the software at all. Following this

procedure STRmix is being continually checked against

human expectations and hence is being continually

validated"; is that correct?---That's reasonable, yes.

I'm concentrating more on the first sentence within the

paragraph, as I read it, it is you the developer's

preferred procedure that the biologist actually assesses

the person of interest's profile first before employing

STRmix?---Or before looking at the STRmix results.

You go on to say - - - ?---I was just going to elaborate on

that. If you form your, what you believe to be the case,

so someone being included in a mixture or excluded in a

mixture or whether it is difficult to say first, then you

can objectively assess the STRmix output in the

likelihood ratio, which is why we always suggest you form


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your opinions before looking at the STRmix results rather

than looking at the STRmix results, because the risk is

if you look at the STRmix results and STRmix says or

gives a likelihood ratio that supports their inclusion

you may then be biased to go oh, yes, well, I would have

chosen inclusion anyway. So does that makes sense?

It does, but I would have thought the bias argument would more

exist with your preferred method on the basis there is a

subjective assessment that I have a got a match here

potentially with one of the components of this profile

that I have not yet objectively in a sense independently

analysed with STRmix, what would you say to that?---I

think it is always important to generate your

interpretations before looking at the STRmix results, I

think that's - - -

Do you know if that is done in Victoria by the way, if that

preferred procedure, have you made that specific

recommendation to FSL in Victoria?---I'm not aware of the

specific practices there, no.

Have you made, have you published to FSL in Victoria that's the

preferred practice by you, the developer?---Well, it is

published in that paper you just read out.

I understand that, they may not have the paper, they should

have, is it in the manual, is it the verbal

communications, "look, this is the way you go about it,

up to you ultimately, I am not your supervisor", because

they have training, I would anticipate you probably

either established or participated in establishing the

core product of the training program; is that right?---I

would have, yes, yes, I would have to check the manuals,

the STRmix manuals to see what it says about the way that


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these things were went about.

But if it is not in the manual you would expect it would be

part of the training component for a biologist?---Yes,

and I believe in the training that we give there is a

component of STRmix implementation where we go through

those sorts of things.

Moving on to a slightly different issue, but still within the

paragraphs sensitivity and specificity studies. You say,

to highlight the matter, having said the LR is an

assessment of the weight of evidence, you raise this

issue, "to highlight the matter, consider that we make up

a DNA mixture and hence we know the donor's. Consider

that this mixture is made from Smith and Brown. If we

test the proposition that it contains Smith we expect a

high LR, suppose the LR is a billion, is this correct?

It is larger than one and as such that part is correct,

but is a billion too large or too small or just right?

The problem is that we do not have the 'true answer' and

this cannot be obtained by any method", that's

correct?---Correct.

You then deal with the issue of false exclusions and say, "A

false exclusion occurs when" bullet point (i) "the PCR

reaction runs sufficiently poorly that the peak or

stutter heights give misleading information or" bullet

point (ii) "a non-contributor is assumed to be present

or" bullet point (iii) "there is an operator error

notably inclusion of an artefact in the peak information

used by STRmix at interpretation. An artifactual peak

that has been retained within the input file will become

part of the information used by STRmix to build genotype

combinations. This will result in genotype combinations


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containing the artefact which will not align with the

true genotypes of contributors to the profile. If the

POI aligns with one of these altered (false) genotypes

this might result in a false exclusion". You'd stand by

that?---Yes.

"There are a number of factors within STRmix under the control

of the operator or the lab that affects errors. Most

significantly are the two variance terms",

correct?---Yes.

"If these are set too low they increase false exclusions, set

too high they increase false inclusions"; correct?

---Correct.

"These variances are set during the lab's internal validation

by modelling the observed variation in allelic and

stutter peak heights within a set of single source

profiles of varying quality. There are a number of

diagnostic output by STRmix that allow a human check of

the results including the genotypic weights" - then

there's an equation - "the posterior mean of the variance

terms and summary statistics of the MCMC (discussed

later)." Now, I'll just read out the sentence again.

"The variances are set during the lab's internal

validation by modelling the observed variation in allelic

stutter and stutter peak heights within a set of single

source profiles of varying quality". You then give a

reference of yourself, Buckleton and Bright, "Factors

affecting people height variability for STR repeat data,

FSI Genetics 21 in 2016?---Just before you go on, that's

the paper that I was referring to earlier.

Yes?---That compares mixture and single source profiles.

Thanks for that. But this sentence doesn't refer to mixed


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source profiles. I'll read the sentence again. "These

variances are set during a lab's internal validation by

modelling the observed variation in allelic and stutter

peak heights within a set of single source profiles of

varying quality." I'm inferring the variances are not

set during a lab's internal validation by modelling

observed variation allelic and stutter peak heights not

from a set of complex mixture profiles?---That's right,

so a number of properties of DNA profiles including the

peak height variability and including stutter ratios and

locus amplification efficiency are all set using single

source profiles and there's no reason to believe that any

of those factors would be different if there is more than

one person's DNA in a DNA extract - - -

Okay. Do you have any- - -?---And any tests that we have done

that look at that have indicated there's no difference

between a single source and mixed profiles.

Well, can you identify either now or in the fullness of time

any peer reviewed literature supporting that

statement?---I will do.

Thank you.

HER HONOUR: Is that convenient time, Mr Desmond?

MR DESMOND: Yes, thank you, Your Honour.

HER HONOUR: We will break for lunch until 2.15. Adjourn the

court, please.

<(THE WITNESS WITHDREW)


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LUNCHEON ADJOURNMENT

.DF:DM:CAT 20/04/17 SC 11A 177 DISCUSSIONTuite

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WITNESS AND EXHIBIT LIST: PAGE:

DISCUSSION 119

DUNCAN ALEXANDER TAYLOR, SWORN AND EXAMINED 120

EXHIBIT B - - STATEMENT OF DR DUNCAN TAYLOR DATED 17/4/2015.

120

EXHIBIT C - - STATEMENT OF DR DUNCAN TAYLOR DATED 15/8/2016.

120

CROSS-EXAMINED BY MR DESMOND 120

THE WITNESS WITHDREW 157

DUNCAN ALEXANDER TAYLOR, RECALLED 157

THE WITNESS WITHDREW 176

LUNCHEON ADJOURNMENT 177

DISCUSSION 177

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