1. Statistical weights of single source DNA profiles Forensic Bioinformatics (www.bioforensics.com) Dan E. Krane, Wright State University, Dayton, OH Forensic DNA Profiling Video Series

2. DNA statistics Coincidental 13 locus DNA profile matches are exceedingly rare Several factors can make statistics less impressive –Mixtures –Incomplete information –Relatives

3. DNA profile

4. Comparing electropherograms Evidence sampleSuspect #1’s reference EXCLUDE

5. Comparing electropherograms Evidence sampleSuspect #2’s reference CANNOT EXCLUDE

6. What weight should be given to DNA evidence? Statistics do not lie. But, you have to pay close attention to the questions they are addressing.

7. What weight should be given to DNA evidence? Statistics do not lie. But, you have to pay close attention to the questions they are addressing. RMP: The chance that a randomly chosen, unrelated individual from a given population would have the same DNA profile observed in a sample.

8. Single source samples Formulae for RMP: At a locus: Heterozygotes: Homozygotes: Multiply across all loci p2p2 Statistical estimates: the product rule 2pq p2p2 p2p2 p2p2 xxxx xxxx xxxx x x

9. 0.1454x0.1097x2 Statistical estimates: the product rule

10. 3.2%6.0%4.6%1.2% 9.8%9.5%6.3%2.2%1.0% 2.9%5.1%29.9%4.0% 1.1%6.6% XXXX XXXXX XXXX X Statistical estimates: the product rule 1 in 609,000,000,000,000,000,000 1 in 609 quintillion = 0.0320.14540.10972xx

11. Two underlying assumptions of the product rule: The events being evaluated are independent –In this context, the events are the observation of specific alleles The frequencies of the events are known –In this context, at what frequency does each allele occur?

12. Population genetics: testing for independence Hardy-Weinberg equilibrium (HWE) –A test of the independence of alleles within a locus Linkage equilibrium –A test of the independence of alleles between loci

13. DNA profile

14. DNA statistics Coincidental 13 locus DNA profile matches are exceedingly rare Corrections can be made for population substructure RMP statistics described in terms of quintillions are common

15. Two underlying assumptions of the product rule: The events being evaluated are independent –In this context, the events are the observation of specific alleles The frequencies of the events are known –In this context, at what frequency does each allele occur?

16. What weight should be given to DNA evidence? Statistics do not lie. But, you have to pay close attention to the questions they are addressing. RMP: The chance that a randomly chosen, unrelated individual from a given population would have the same DNA profile observed in a sample.

17. What is the relevant population? 1 in 609 quintillion

18. Popular vote in 2008 by county. McCain won red counties, Obama won blue counties. How would you determine the frequency of Obama supporters in North Carolina? Obama N.C. 50.2%

19. Popular vote in 2008 by county. McCain won red counties, Obama won blue counties. How would you determine the frequency of Obama supporters in North Carolina? Obama N.C. 50.2% Region 59.6%

20. Popular vote in 2008 by county. McCain won red counties, Obama won blue counties. How would you determine the frequency of Obama supporters in North Carolina? Obama N.C. 50.2% Region 59.6% U.S. 52.9%

21. Popular vote in 2008 by county. McCain won red counties, Obama won blue counties. How would you determine the frequency of Obama supporters in North Carolina? Obama N.C. 50.2% Region 59.6% U.S. 52.9% Utah? 35.5% ?

22. DNA statistics Coincidental 13 locus DNA profile matches are exceedingly rare Several factors can make statistics less impressive –Mixtures –Incomplete information –Relatives

23. Statistical weights of single source DNA profiles Forensic Bioinformatics (www.bioforensics.com) Dan E. Krane, Wright State University, Dayton, OH Forensic DNA Profiling Video Series