1. Establishing parameters for objective interpretation of DNA profile evidence Forensic Bioinformatics (www.bioforensics.com) Dan E. Krane, Wright State University, Dayton, OH Steelman Visiting Scientist Lecture Series, Lenoir-Rhyne University, April 9, 2010

2. The science of DNA profiling is sound. But, not all of DNA profiling is science.

3. The science of DNA profiling is sound. There is plenty of opportunity for improvement.

4. The science of DNA profiling is sound. There is plenty of opportunity for improvement. I. Interpretation II. Statistical weighting

5. Doesnt someone either match or not?

6. Opportunities for subjective interpretation? Who can be excluded? SuspectD3vWAFGA Tom17, 1715, 1725, 25 Dick12, 1715, 1720, 25 Harry14, 1715, 1720, 25 Sally12, 1715, 1520, 22

7. Signal Measure μbμb μ b + 3σ b μ b + 10σ b Mean background Signal Detection limit Quantification limit Measured signal (In Volts/RFUS/etc) Saturation 0

8. Many opportunities to measure baseline

9. Measurement of baseline in control samples: Negative controls: 5,932 data collection points (DCPs) per run ( = 131 DCPs) Reagent blanks: 5,946 DCPs per run ( = 87 DCPs) Positive controls: 2,415 DCP per run ( = 198 DCPs)

10. RFU levels at all non-masked data collection points

11. Variation in baseline noise levels Average ( b ) and standard deviation ( b ) values with corresponding LODs and LOQs from positive, negative and reagent blank controls in 50 different runs. BatchExtract: ftp://ftp.ncbi.nlm.nih.gov/pub/forensics/

12. Lines in the sand: a two-person mix? Two reference samples in a 1:10 ratio (male:female). Three different thresholds are shown: 150 RFU (red); LOQ at 77 RFU (blue); and LOD at 29 RFU (green).

13. Mixed DNA samples

14. How many contributors to a mixture if analysts can discard a locus? How many contributors to a mixture? Maximum # of alleles observed in a 3-person mixture # of occurrencesPercent of cases 200.00 3780.00 44,967,0343.39 593,037,01063.49 648,532,03733.12 There are 146,536,159 possible different 3-person mixtures of the 959 individuals in the FB I database (Paoletti et al., November 2005 JFS). 3,398 7,274,823 112,469,398 26,788,540 0.00 4.96 76.75 18.28

15. How many contributors to a mixture if analysts can discard a locus? How many contributors to a mixture? Maximum # of alleles observed in a 3-person mixture # of occurrencesPercent of cases 200.00 33100.00 42,498,1395.53 529,938,77766.32 612,702,67028.14 There are 45,139,896 possible different 3-person mixtures of the 648 individuals in the MN BCI database (genotyped at only 12 loci). 8,151 1,526,550 32,078,976 11,526,219 0.02 3.38 71.07 25.53

16. How many contributors to a mixture? Maximum # of alleles observed in a 4-person mixture # of occurrencesPercent of cases 413,4800.02 58,596,32015.03 635,068,04061.30 712,637,10122.09 8896,4351.57 There are 57,211,376 possible different 4-way mixtures of the 194 individuals in the FB I Caucasian database (Paoletti et al., November 2005 JFS). (35,022,142,001 4-person mixtures with 959 individuals.)

17. The science of DNA profiling is sound. There is plenty of opportunity for improvement. I. Interpretation II. Statistical weighting

18. 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.

19. 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.

20. 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.

21. Consider cold hits CODIS (Combined Offender DNA Index System) Maintained by the FBI Contains 7,940,321 profiles as of February, 2010. Assisted in 109,900 investigations

22. What weight should be given to DNA evidence? Probable Case –Suspect is first identified by non-DNA evidence –DNA evidence is used to corroborate traditional police investigation Cold Hit Case –Suspect is first identified by search of DNA database –Traditional police work is no longer focus Which is more damning evidence?

23. What weight should be given to DNA evidence? Probable Case –Suspect is first identified by non-DNA evidence –DNA evidence is used to corroborate traditional police investigation –RMP = 1 in 10 million Cold Hit Case –Suspect is first identified by search of DNA database –Traditional police work is no longer focus –RMP = 1 in 10 million Which is more damning evidence?

24. What weight should be given to DNA evidence? Probable Case –Suspect is first identified by non-DNA evidence –DNA evidence is used to corroborate traditional police investigation –RMP = 1 in 10 million Cold Hit Case –Suspect is first identified by search of DNA database –Traditional police work is no longer focus –RMP = 1 in 10 million –DMP = roughly 4 in 5 Which is more damning evidence?

25. 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.

26. What is the relevant population? 1 in 80 quadrillion

27. 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%

28. 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%

29. 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%

30. 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% ?

31. What is the relevant population? Errors are multiplicative

32. 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.

38. Combined probability of inclusion (CPI): a cousin of the RMP What fraction of a population cannot be excluded as a possible contributor to a given mixture?

39. Combined probability of inclusion (CPI): a cousin of the RMP What fraction of a population cannot be excluded as a possible contributor to a given mixture? What fraction of the population cannot be excluded from contributing their DNA to a given mixture if they are allowed to not match at two loci?

40. Matching profiles in NIST database PopulationSample IDD21 1D21 2D7 1D7 2CSF 1CSF 2D13 1D13 2D16 1D16 2D2 1D2 2D18 1D18 2FGA 1FGA 2Matching Loci African AmericanGT3717028 1011121411 2225121822237 African AmericanOT0589630 10 1112 11 202218 19257 African AmericanPT838913032.211 12 11 1922121622237 African AmericanPT8391228 10118 12911172516 22 7 African AmericanGT371692932.210 71112 9111920141823266 African AmericanMT95356283011 12 9 22 151821236 African AmericanZT7961732.233.17121012 9112025121421 6 CaucasianGT3687728309911 9 1822161820266 CaucasianGT3807530 101312 11 1921121422236 CaucasianMT948802829101112 11121112202516 22236 CaucasianWT524803031810111211129925 16 21 6 n = 257 African Americans, 302 Caucasians (1 in 21 African Americans; 1 in 38 Caucasians)

41. The science of DNA profiling is sound. There is plenty of opportunity for improvement. (particularly in the areas of interpretation and attaching statistical weights)