How True Allele Works Part 3 Kinship Paternity

Kinship Task. Infer genotypes and match them Tool. Bayes theorem Data. Genotypes of family

Pedigree father F mother M person X child 1 C 1 spouse S child

Prior probability How a variable is affected father F aa mother M ab person

Prior probability father F aa mother M bc person X Punnett square b c

Likelihood How a variable affects others person X spouse S bb child C ab

Likelihood person spouse X S aa bb aa child aa C ab

Posterior probability father F aa mother M bc person spouse X S bb child

Genotype comparison alleged person A ab father F aa mother M bc person spouse

Bayes theorem, second round Hypothesis: The missing and reference persons are the same individual

Paternity biological father X spouse S child C

Genotype comparison alleged father biological father A X spouse S child C

Paternity index 10, 10 LR = 3. 28 log(LR) = 0. 52

Maternity question biological mother X child C alleged mothers A 1 A 4 A

Biological mother genotype biological mother X child C

Identifying the mother A 1 A 2 A 3 A 4 A 5 A

Missing person 1 person X child 1 C 1 1+2 child 3 C 2

Children + Spouse 1 person X child 1 C 1 spouse S child 2

Parents + Children father F mother M person X child 1 C 1 1

Parents + Children + Spouse father F mother M person X child 1 C

Mixture + Kinship genotypes CSF 1 PO Separated minor contributor Kinship inferred son Random

Contributor genotype match LR = 39, 700 log(LR) = 4. 60 mixture kinship population

How True. Allele Works Part 1, 16 -Oct-2014 Genotype modeling and the likelihood ratio

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Kinship Task. Infer genotypes and match them Tool. Bayes theorem Data. Genotypes of family members

Bayes theorem

Pedigree father F mother M person X child 1 C 1 spouse S child 2 child 3 C 2 C 3

Prior probability How a variable is affected father F aa mother M ab person X

Prior probability father F aa mother M bc person X Punnett square b c a ab ac X = ab 1/2 ac 1/2

Likelihood How a variable affects others person X spouse S bb child C ab

Likelihood person spouse X S aa bb aa child aa C ab

Posterior probability father F aa mother M bc person spouse X S bb child C ab

Genotype comparison alleged person A ab father F aa mother M bc person spouse X S bb child C ab

Bayes theorem, second round Hypothesis: The missing and reference persons are the same individual Posterior to prior genotype probability ratio (Essen-Moller, 1938).

Match strength

Paternity biological father X spouse S child C

Paternity genotype D 7 S 820

Genotype comparison alleged father biological father A X spouse S child C

Paternity index 10, 10 LR = 3. 28 log(LR) = 0. 52

LR = 258, 000 log(LR) = 5. 41 Paternity

Maternity question biological mother X child C alleged mothers A 1 A 4 A 2 A 5 A 3 A 6

Biological mother genotype biological mother X child C

Identifying the mother A 1 A 2 A 3 A 4 A 5 A 6

Missing person 1 person X child 1 C 1 1+2 child 3 C 2 C 3 1+2+3

Children + Spouse 1 person X child 1 C 1 spouse S child 2 child 3 C 2 C 3 1+2+3

Parents + Children father F mother M person X child 1 C 1 1 1+2 child 3 C 2 C 3 1+2+3

Parents + Children + Spouse father F mother M person X child 1 C 1 spouse S child 2 child 3 C 2 C 3 1 1+2+3

DNA mixture

Mixture + Kinship father F person X

Mixture + Kinship genotypes CSF 1 PO Separated minor contributor Kinship inferred son Random person

Contributor genotype match LR = 39, 700 log(LR) = 4. 60 mixture kinship population -18. 00 -20. 58 -20. 66 -20. 76 -22. 00 -24. 97 -26. 00 -28. 00

How True. Allele Works Part 1, 16 -Oct-2014 Genotype modeling and the likelihood ratio Part 2, 20 -Nov-2014 Degraded DNA and allele dropout Part 3, 18 -Dec-2014 Kinship, paternity and missing persons Part 4, 15 -Jan-2015 Genotype database and DNA investigation http: //www. cybgen. com/information/webinar/page. shtml perlin@cybgen. com