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1 Familias Thore Egeland, Rikshospitalet and Section of Medical Statistics Joint work with P. Mostad, NR, B. Olaisen, B. Mevåg, M. Stenersen, Inst of Forensic.

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Presentation on theme: "1 Familias Thore Egeland, Rikshospitalet and Section of Medical Statistics Joint work with P. Mostad, NR, B. Olaisen, B. Mevåg, M. Stenersen, Inst of Forensic."— Presentation transcript:

1 1 Familias Thore Egeland, Rikshospitalet and Section of Medical Statistics Joint work with P. Mostad, NR, B. Olaisen, B. Mevåg, M. Stenersen, Inst of Forensic Medicine.

2 2 Innhold Bakgrunn: Utvikling av programmet Familias for rettsgenetiske beregninger Metodisk bakgrunn. Demonstrasjon.

3 3 Ambitions We would like to: - determine most likely family among many, - include non-DNA data (prior), e.g. age, - m odel mutations, - model kinship (departures from Hardy-Weinberg).

4 4

5 5 Bayesian solution Find a set of “possible” pedigrees Set up prior probabilities based on non-DNA information. Compute for each pedigree Make inferences from the posterior distribution:

6 6 H 1 : M1 father H 2 : Unknown man father Posterior probability A,AB,B A,B M1 F1 M2 P(H 1 |data)= Flat prior

7 7

8 8 Prior distribution

9 9 Modelling mutations Mutation rate varies with –Sex of parent and locus. Alleles tend to mutate to close alleles:

10 10 Kinship and uncertainty in allele frequencies Vector of allele frequencies p Dirichlet by evolutionary argument data|p ~ Multinomial Then p|data ~ Dirichlet Basis for simulation

11 11 Kinshipparameter Ped 2, mest sannsynlige, svarer til tidligere figur

12 12 Literature Evett og Weir. "Interpreting DNA evidence". Sinauer, MA, USA, Egeland, Mostad, Mevåg og Stenersen. "Beyond traditional paternity and identification cases. Selecting the most probable pedigree". Forensic Science International, 110(1), 2000 Egeland and Mostad. SJS, 2002.


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