More informative DNA identification: Computer reinterpretation of existing data Ria David, PhD Cybergenetics, Pittsburgh, PA Cybergenetics © 2003-2010.

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Presentation transcript:

More informative DNA identification: Computer reinterpretation of existing data Ria David, PhD Cybergenetics, Pittsburgh, PA Cybergenetics © Midwestern Association of Forensic Scientists 39th Annual Meeting October, 2010

SWGDAM 2010 SWDGAM guidelines, section If a stochastic threshold based on peak height is not used in the evaluation of DNA typing results, the laboratory must establish alternative criteria (e.g., quantitation values or use of a probabilistic genotype approach) for addressing potential stochastic amplification. The criteria must be supported by empirical data and internal validation and must be documented in the standard operating procedures.

TrueAllele ® Casework Computer interpretation of DNA evidence by mathematically modeling STR process objectivity objectivity ease of use ease of use information information productivity productivity Primary goals

Interpretation Matters National Institute of Standards and Technology Two Contributor Mixture Data, Known Victim 31 thousand (4) 213 trillion (14)

Preserving DNA Information Quantitative vs. Qualitative

Data Classification Mixture items assigned a degree of difficulty Simple: two person mixture with a known victim Medium: two unknown mixture samples Complex: three or more unknown contributors, or a partial profile

Information - two unknown

Information - all mixtures

Locus D21S11

Quantitative TrueAllele

Qualitative Threshold

Stochastic Threshold

13 Locus Statistic

Conclusion Forensic analysts’ goal is to get identification information from their data to help solve cases SWGDAM guidelines make it more difficult for analysts to extract information from DNA data TrueAllele’s approach of probabilistic interpretation is allowed by the SWGDAM guidelines and extracts more identification information than human interpretation Using a probabilistic genotype interpretation would enable forensic analysts to better ensure public safety

Acknowledgements New York State Police Barry Duceman Melissa Lee Shannon Morris Elizabeth Staude Cybergenetics William Allan Meredith Clarke Matthew Legler Jessica Smith Cara Spencer Northeast Regional Forensics Institute Jamie Belrose