Exploring Forensic Scenarios with TrueAllele ® Mixture Automation 59th Annual Meeting American Academy of Forensic Sciences February, 2007 Mark W Perlin,

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Presentation transcript:

Exploring Forensic Scenarios with TrueAllele ® Mixture Automation 59th Annual Meeting American Academy of Forensic Sciences February, 2007 Mark W Perlin, PhD, MD, PhD Pittsburgh, PA USA Cybergenetics © Employee, Shareholder, and Discussion of Commercial Products or Services

So many cases, so little time meeting the data challenge review years DNA data generate

Do the best job possible Look at all the good data Ignore the bad data Consider every possibility Obtain the most match information

DNA evidence person

DNA evidence person specimen

DNA evidence person specimenSTR data

DNA evidence person specimenSTR dataprofile

DNA evidence person specimenSTR dataprofile

Consider every possibility every allele call all mixing weights stochastic effects stutter artifact peak imbalance specimen combinations

DNA profile ambiguity data a b abab bb Use wild card [* b] List possibilities [a b], [b b] Attach probability

Match DNA profiles Match Information logarithm – Very large number: “billion billion” or Use the exponent: 18 Match Information = Prob(specific) Prob(random)

Comparing interpretation via match information Wildcards 11.9 Listing 15.9 Probability 17.2 Information

Scientific calculator interpret DNA match DNA database engine

Linear Mixture Analysis J Forensic Sci (6)

"What if...?" scenarios process additional samples? which samples should be used? is there too much data? discard low quality data? combine low signal data? solve serial crimes? how many mixture contributors?

Obtain DNA data

Infer DNA profile

Match DNA profile 17.3

How many contributors? "What if" scenarios

Discard bad data

Low-level informative data

Using informative data 7.9

Using informative data

Combine informative data 12.9

Serial crime investigation 12.9

Many sample combinations Which subset of DNA samples gives the most informative result? seven groupings

TrueAllele scientific calculator 20 interpret CPUs 1 match computer central database database interpret match

Combining low level data seven groupings

Do the best job possible Look at all the good data Ignore the bad data Consider every possibility Obtain the most match information