Forensic Bioinformatics (bioforensics)

1. Suspect-Centric Combined Probability of InclusionA means of attaching objective statistical weights to mixed DNA profiles where dropout may have occurred Forensic Bioinformatics (www.bioforensics.com) Dan E. Krane, Ph.D., Wright State University, Dayton, OH

2. The problems with mixtures where dropout may have occurred • Determining the rate of allelic dropout is problematic • Interpreting evidence in a way that is least favorable to a defendant is taboo

3. CPI statistics without dropout

4. Combined Probability of Inclusion CPI statistics without dropout • Probability that a random, unrelated person could be included as a possible contributor to a mixed profile • For a mixed profile with the alleles 14, 16, 17, 18; contributors could have any of 10 genotypes: 14, 1414, 16 14, 17 14, 18 16, 1616, 17 16, 18 17, 1717, 18 18, 18 Probability works out as: CPI = (p[14] + p[16] + p[17] + p[18])2 (0.102 + 0.202 + 0.263 + 0.222)2 = 0.621

7. The testing lab’s conclusions

10. Ignoring loci with “missing” alleles • Some laboratories assert that this is a “conservative” approach • Ignores potentially exculpatory information • “It fails to acknowledge that choosing the omitted loci is suspect-centric and therefore prejudicial against the suspect.” • Gill, et al. “DNA commission of the International Society of Forensic Genetics: Recommendations on the interpretation of mixtures.” FSI. 2006.

11. Mixtures where allelic drop out may have occurred • Determining the rate of allelic drop out is problematic • Interpreting evidence in a way that is least favorable to a defendant is taboo

12. Mixtures where allelic drop out may have occurred • Determining the rate of allelic drop out is problematic • Interpreting evidence in a way that is least favorable to a defendant is taboo • What if instead of trying to assess drop out we invoke it liberally? • What if instead of trying to eliminate knowledge of a reference profile we embrace it?

13. Mixtures where allelic drop out may have occurred • Determining the rate of allelic drop out is problematic • Interpreting evidence in a way that is least favorable to a defendant is taboo • What if instead of trying to assess drop out we invoke it liberally? • What if instead of trying to eliminate knowledge of a reference profile we embrace it? • How does a given suspect compare to 1,000,000 random individuals who are treated the same way?

14. 1,000 1 10 100 10,000 100,000 1/Suspect-centric CPI

15. 1,000 1 10 100 10,000 100,000 1/Suspect-centric CPI

16. B: 10,482 A: 902 1,000 1 10 100 10,000 100,000 1/Suspect-centric CPI

20. 1,000 1 10 100 10,000 100,000 1/Suspect-centric CPI

21. 1,000 1 10 100 10,000 100,000 1/Suspect-centric CPI

22. 48,564 1,000 1 10 100 10,000 100,000 1/Suspect-centric CPI

23. 1,000 1 10 100 10,000 100,000 1/Suspect-centric CPI

24. Mixtures where allelic drop out may have occurred • Determining the rate of allelic drop out is problematic • Interpreting evidence in a way that is least favorable to a defendant is taboo • What if instead of trying to assess drop out we invoke it liberally? • What if instead of trying to eliminate knowledge of a reference profile we embrace it? • How does a given suspect compare to 1,000,000 random individuals who are treated the same way?

25. Suspect-Centric Combined Probability of Inclusion Dan E. Krane, Ph.D., Wright State University, Dayton, OH Forensic Bioinformatics (www.bioforensics.com)