1. Familias and Forensic genetics Thore. Egeland@umb
Familias and Forensic genetics Norwegian University of Life Sciences San Andrés Island, June 4, 2012
Presentation
Leonor
Petter Mostad, Daniel Kling
Title:
Famlias
1995: Pater
2011, Familias 2.0 (1.97)
2012 Code also released Open Familias (R)
Forensic genetics:
Statistical aspects emphasized; most of you know more of the technical, or lab aspects
Kinship problems, not crime (mixtures)
Your background?
My backgroun

2. Purpose
"..practical workshop about the statistical evaluation of forensic cases (paternity and other family relationships) by using Familias"
Quoted from the mandate
Key-words:
Practical.
Exercises. Focus on Familias Software. Case work
Little/no mathematics
Statistical evaluation:
Useful also if you choose to report only on a verbal scale

3. Contents Principles Statistical evaluation Familias. Exercises
LR (Paternity index)
Non-standard cases
Theta-correction
Mutations
Complex pedigrees
Silent alleles.
Familias. Exercises
Course homepage arken.umb.no/~theg/familias/ user: familias pass word: andres
Principles: Just a little bit. There is an underlying philosphy, science:
”Look to DNA”, i.e., other forensic disciplines are not as well founded
Non-standard cases: Software is needed
Exercises: Practical hands on exercises Homepage 9: :00 Review of basic forensic genetics.  Principles. LR for simple cases. Spanish/Portuguese summary. 10: :15 Introduction to Familias. Demo. Spanish/Portuguese summary
11:15 - 11:45 Coffee break
11: :30 Familias exercises.
Participants will use computer with Familias installed.
12: :00 Lunch
14: :00 Non-standard cases. Spanish/Portuguese summary.
Complex relationships. Mutation. Theta-correction 16: :00 Familias exercises.
17:00- 18:00 Discussion of exercises. Spanish/Portuguese summary.
More questions, contributions from participants.

4. Review of basic forensic genetics Spanish/Portuguese summary
Part I: 09-10
Review of basic forensic genetics
Spanish/Portuguese summary
Practicalities ended: Leonor: Review so far?

5. Books: Evett&Weir, Balding, Buckleton et al.
Principles
To evaluate the uncertainty of any given proposition it is necessary to consider at least one alternative proposition.
Scientific interpretation is based on questions of the kind: “What is the probability of the evidence given the proposition?”
Scientific evidence is conditioned not only by the competing propositions, but also by the framework of circumstances within which they are to be evaluated
Why not only ”Man is the father”?
Evaluation of evidence depends on alternative
Alternative: ”unrelated”: Typically strong evidence
Alternative: brother of AF: Typically weaker evidence
Reporting officer: statements about DNA given proposition Court, Decision maker: statements about proposition given DNA
What is the alternative? Need to know something about the case. ”All probabilities are conditional”
Books: Evett&Weir, Balding, Buckleton et al.
RMI

6. Exercise S1 Standard paternity case
H1: The alleged father (AF) is the real father
H2: AF and the child are unrelated.
Most basic ideas can be illustrated by this simple example.
There are alternatives to notation and formulation
Explain notation

7. Exercise S1 a) Calculate LR. First marker
Probabilities 0-1 (or 0-100%, not used in calculation)
Conditional probabilities
Explain LR
pA close to 0: Strong evidence
pA>>0: Weaker evidence
0.05 : From where?
Interpretation: Numbers of verbal scale?
Observe that we have used principles 1,2, and 3.
Before next slide:
Q: What is special , unique with DNA? Compared to say fingerprints
A: Ther is lot of independent data
Interpretation: “The data is 20 times more likely assuming
AF to be the father compared to the alternative
that some unknown man is the father”.

8. Exercise S1 c) Calculate LR. Second marker
Only slightly more difficult
Table, excel can cover all cases of genotype combinations.

9. Exercise S1 c) Calculate LR. Two markers
Assumptions
HW. Within marker. This is a bit hidden without more mathematics, but we have used that what is passed down from mother and father is independent and this inependence assumption is secured by HW
LE. Linkage equilibrium
No artefacts (mutation, silent alleles, genotyping errors)
Interpretation: “The data is 200 times more likely assuming
AF to be the father compared to the alternative
that some unknown man is the father”.
Assumptions?

10. Non-standard cases Complications Theta-correction Mutations
Complex pedigrees
Silent alleles
Later

11. Part II: 10-1115: Introduction to Familias. Demo.
Exercises S1-S3, S5. Plenum
Videos available
Spanish/Portuguese summary
Leonor: review!i
As videos 1-3; deliberately present mutations before we discuss in more detail

12. Part III: 1145-1230: Hands on Familias exercises
Exercises S1-S6

13. Part IV: 14-16 Repetition. Exercises S4, S6. Plenum Non-standard cases

14. Non-standard cases Complications Theta-correction Mutations
Complex pedigrees
Silent alleles
Need software
How to deal with four major complications in Familias

15. Theta - correction
Corrects for deviations from Hardy-Weinberg-Equilibrium
What is HWE?
Dependence between the two alleles
Theta models this dependence
Theta
Theta>0 : if allele A is seen many times , the probability of seing A again increases
Longer story
Hardy-Weinberg may not be valid for a number of reasons including non-random mating. At the simplestl evel the theta correction can be considered to correct for deviation from HW. Theta is between 0 and 1 and for 0 the usual results obtained assuming HW would apply. For theta>0 we see that the there is an excess of homozygotes (actually simple estimates of theta can be based on the difference betweenobserved and expected number of heterozygotes).

16. Revisit Exercise S1h (plenum)
Only kinship, theta, parameter used in this window
Revisit Exercise S1h (plenum)

17. Modelling mutations Mutation rate varies with
Sex of parent and locus. Alleles tend to mutate to close alleles:
Several models
Assume a laboratory handles 1000 cases a year. With 10 markes and two meioses for each case, we would have something like
1000*10*2*0.005=100 mutations with an average mutation rate of 0,005.
It’s hard to deal analytically with mutations and this was our original motviation for developing software.
There are some ad-hoc mutations models around (at least I consider to to be ad hoc, since they tend not be based on a proper model.)

18. Mutations Revisit Exercise S2, S7 Females versus males
Stable versus non-stable
First two require two parameters
Second two require only one
Revisit Exercise S2, S7

19. Complex pedigrees I. Exercise S6

20. Complex pedigrees II. Exercise S6

21. Silent alleles I. Exercise S11
Silent alleles, null alleles

22. Silent alleles II. Familias=1

23. Silent alleles III. Exercises S11 (S12 theoretical)

24. Part V: Hands on exercises: S9, S10, S11 If time: 'Extra' exercises on homepage: arken.umb.no/~theg/familias/

25. Part VI: 17-18 Discussion of exercises. Spanish/Portuguese summary.
Questions?
Exercises S1h, S4c, S5d, S9d
S1h ”Discuss the assumptions underlying the calculations of this exercise:
HWE; if not theta corrrection LD
Mutations, silent alleles
Other? Forensic markers are non-coding
S4c: GF and GS share the same haplotype, freq
LR=1/0.0025=400. Multiply 3.4? Problem: Y-based LR refers to different hypothesis;
Could replace GF by say a brother and GS by say a brother
S5d: W easier to interpret? Problem: prior. Why 50-50?
S9d: Is there a best mutation model?
Balance practical demands and theoretical demands
Should a mutation model be used routinely for all markers?
Case for YES: Should not adjust model once specifics of a case materialise

26. References
Familias reference: Egeland, Mostad et al., see also