DNA Identification: Mixture Weight & Inference

Slides:

Advertisements

Similar presentations

DNA Identification: TrueAllele ® Testimony Cybergenetics © Continuing Legal Education Duquesne University October, 2010 Mark W Perlin, PhD, MD,

Advertisements

Overcoming DNA Stochastic Effects 2010 NEAFS & NEDIAI Meeting November, 2010 Manchester, VT Mark W Perlin, PhD, MD, PhD Cybergenetics, Pittsburgh, PA Cybergenetics.

Sherlock Holmes and the DNA Likelihood Ratio American Academy of Forensic Sciences February, 2011 Chicago, IL Mark W Perlin, PhD, MD, PhD Cybergenetics,

Forensic DNA Inference ICFIS 2008 Lausanne, Switzerland Mark W Perlin, PhD, MD, PhD Joseph B Kadane, PhD Robin W Cotton, PhD Cybergenetics ©

DNA Identification as an Information Science

DNA Mixture Interpretations and Statistics – To Include or Exclude Cybergenetics © Prescription for Criminal Justice Forensics ABA Criminal Justice.

Combining DNA Evidence for Greater Match Information

Finding Truth in DNA Mixture Evidence Innocence Network Conference April, 2013 Charlotte, NC Mark W Perlin, PhD, MD, PhD Cybergenetics, Pittsburgh, PA.

TrueAllele ® Challenges in Court and Culture Cybergenetics © th Annual DNA Technology Educational Seminar Centre of Forensic Sciences and the.

How Inclusion Interpretation of DNA Mixture Evidence Reduces Identification Information American Academy of Forensic Sciences February, 2013 Washington,

Creating informative DNA libraries using computer reinterpretation of existing data Northeastern Association of Forensic Scientists November, 2011 Newport,

Preventing rape in the military through effective DNA computing Forensics Europe Expo Forensics Seminar Theatre April, 2014 London, UK Mark W Perlin, PhD,

Coding a Safer Society through Computer Interpretation of DNA Evidence Cybergenetics © MATLAB Virtual Conference March, 2014 Mark W Perlin, PhD,

Probabilistic Software Workshop September 29, 2014 TrueAllele® Casework Mark W. Perlin, PhD, MD, PhD.

TrueAllele ® Interpretation of DNA Mixture Evidence 9 th International Conference on Forensic Inference and Statistics August, 2014 Leiden University,

How TrueAllele® Works (Part 1)

Probabilistic Software Workshop September 29, 2014

TrueAllele ® Casework Validation on PowerPlex ® 21 Mixture Data Australian and New Zealand Forensic Science Society September, 2014 Adelaide, South Australia.

Using TrueAllele ® Casework to Separate DNA Mixtures of Relatives California Association of Criminalists October, 2014 San Francisco, CA Jennifer Hornyak,

No DNA Left Behind: When "inconclusive" really means "informative" Schenectady County District Attorney’s Office January, 2014 Mark W Perlin, PhD, MD,

Revolutionising DNA analysis in major crime investigations The Investigator Conferences Green Park Conference Centre May, 2014 Aylesbury, Buckinghamshire.

TrueAllele ® Mixture Interpretation Cybergenetics © th Annual DNA Technology Educational Seminar Centre of Forensic Sciences and the Promega.

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

Scientific Validation of Mixture Interpretation Methods 17th International Symposium on Human Identification Sponsored by the Promega Corporation October,

Computer Interpretation of Uncertain DNA Evidence National Institute of Justice Computer v. Human June, 2011 Arlington, VA Mark W Perlin, PhD, MD, PhD.

Touch DNA in the Massereene Attack Cybergenetics © Continuing Legal Education Allegheny County Courthouse February, 2012 Mark W Perlin, PhD,

TrueAllele ® Modeling of DNA Mixture Genotypes California Association of Crime Laboratory Directors October, 2014 San Francisco, CA Mark W Perlin, PhD,

How TrueAllele ® Works (Part 2) Degraded DNA and Allele Dropout Cybergenetics Webinar November, 2014 Mark W Perlin, PhD, MD, PhD Cybergenetics, Pittsburgh,

TrueAllele ® Genetic Calculator: Implementation in the NYSP Crime Laboratory NYS DNA Subcommittee May 19, 2010 Barry Duceman, Ph.D New York State Police.

Reanimating Zombie™ DNA Penn State Dickinson Law School September, 2012 State College, Pennsylvania Mark W Perlin, PhD, MD, PhD Cybergenetics, Pittsburgh,

Separating Familial Mixtures, One Genotype at a Time Northeastern Association of Forensic Scientists November, 2014 Hershey, PA Ria David, PhD, Martin.

Cybergenetics Webinar January, 2015 Mark W Perlin, PhD, MD, PhD Cybergenetics, Pittsburgh, PA Cybergenetics © How TrueAllele ® Works (Part 4)

Cracking the DNA mixture code – computer analysis of UK crime cases Forensics Europe Expo Forensic Innovation Conference April, 2014 London, UK Mark W.

Unleashing Forensic DNA through Computer Intelligence Forensics Europe Expo Forensic Innovation Conference April, 2013 London, UK Mark W Perlin, PhD, MD,

Rapid DNA Response: On the Wings of TrueAllele Mid-Atlantic Association of Forensic Scientists May, 2015 Cambridge, Maryland Martin Bowkley, Matthew Legler,

Getting Past First Bayes with DNA Mixtures American Academy of Forensic Sciences February, 2014 Seattle, WA Mark W Perlin, PhD, MD, PhD Cybergenetics,

Compute first, ask questions later: an efficient TrueAllele ® workflow Midwestern Association of Forensic Scientists October, 2014 St. Paul, MN Martin.

TrueAllele ® interpretation of Allegheny County DNA mixtures Cybergenetics © Continuing Legal Education Allegheny County Courthouse February,

Virginia TrueAllele ® Validation Study: Casework Comparison Presented at AAFS, February, 2013 Published in PLOS ONE, March, 2014 Mark W Perlin, PhD, MD,

TrueAllele ® Computing: All the DNA, all the time Continuing Professional Development Sydney, Australia March, 2014 Mark W Perlin, PhD, MD, PhD Cybergenetics,

Murder in McKeesport October 25, 2008 Tamir Thomas.

When Good DNA Goes Bad International Conference on Forensic Research & Technology October, 2012 Chicago, Illinois Mark W Perlin, PhD, MD, PhD Cybergenetics,

DNA Mapping the Crime Scene: Do Computers Dream of Electric Peaks? 23rd International Symposium on Human Identification October, 2012 Nashville, TN Mark.

Mark W Perlin, PhD, MD, PhD Cybergenetics, Pittsburgh, PA Cybergenetics © Duquesne University October, 2015 Pittsburgh, PA What’s in a Match?

Open Access DNA Database Duquesne University March, 2013 Pittsburgh, PA Mark W Perlin, PhD, MD, PhD Cybergenetics, Pittsburgh, PA Cybergenetics ©

Jack Ballantyne and Mark Perlin International Conference on Inference and Statistics, July , Seattle, WA.

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

Objective DNA Mixture Information in the Courtroom: Relevance, Reliability & Acceptance NIST International Symposium on Forensic Science Error Management:

DNA Identification: Quantitative Data Modeling Cybergenetics © Mark W Perlin, PhD, MD, PhD Cybergenetics, Pittsburgh, PA TrueAllele ® Lectures.

DNA-led investigation through computer interpretation of evidence Pennsylvania State Police Training Seminar Hershey, PA April, 2014 Mark W Perlin, PhD,

Data summary – “alleles” Threshold Over threshold, peaks are labeled as allele events All-or-none allele peaks, each given equal status Allele Pair 8,

Generalization Performance of Exchange Monte Carlo Method for Normal Mixture Models Kenji Nagata, Sumio Watanabe Tokyo Institute of Technology.

DNA: TrueAllele® Statistical Analysis, Probabilistic Genotyping

A Match Likelihood Ratio for DNA Comparison

Explaining the Likelihood Ratio in DNA Mixture Interpretation

Distorting DNA evidence: methods of math distraction

Virginia TrueAllele® Validation Study: Casework Comparison

Mark W Perlin, PhD, MD, PhD Cybergenetics, Pittsburgh, PA, USA

American Academy of Forensic Sciences Criminalistics Section

Solving Crimes using MCMC to Analyze Previously Unusable DNA Evidence

Investigative DNA Databases that Preserve Identification Information

DNA Identification: Inclusion Genotype and LR

DNA Identification: Stochastic Effects

Mark W Perlin, PhD, MD, PhD Cybergenetics, Pittsburgh, PA, USA

DNA Identification: Biology and Information

DNA Identification: Biology and Information

severed carotid artery

DNA Identification: Biology and Information

DNA Identification: Mixture Interpretation

Presentation transcript:

DNA Identification: Mixture Weight & Inference Mark W Perlin, PhD, MD, PhD Cybergenetics, Pittsburgh, PA TrueAllele® Lectures Fall, 2010 Cybergenetics © 2003-2010 Cybergenetics © 2003-2010

Mixture Weight: Uncertain Quantity Infer mixture weight from STR experiments: • quantitative peak data • contributor genotypes Pr(W=w | data, G1=g1, G2=g2, …) hierarchical Bayesian model Perlin MW, Legler MM, Spencer CE, Smith JL, Allan WP, Belrose JL, Duceman BW. Validating TrueAllele® DNA mixture interpretation. Journal of Forensic Sciences. 2011;56(November):in press. Cybergenetics © 2003-2010

Mixture Weight Model kth contributor experiment data dk,1 dk,2 … dk,N locus weights Wk,1 Wk,2 … Wk,N template weight Wk prior probability W0 Cybergenetics © 2003-2010

Experiment Estimate sum of peak heights from kth contributor wk = from all contributors Cybergenetics © 2003-2010

D16S539 Cybergenetics © 2003-2010

Three Alleles Allele 11 12 13 Quantity 500 6,750 250 11 12 13 Cybergenetics © 2003-2010

Experiment Estimate Allele 11 12 13 Quantity 500 6,750 250 500 + 250 500 + 6,750 + 250 750 11 12 13 = = 10% 7,500 Cybergenetics © 2003-2010

D7S820 Cybergenetics © 2003-2010

Four Alleles Allele 8 10 12 13 Quantity 4,000 250 3,000 8 10 12 13 Cybergenetics © 2003-2010

Experiment Estimate Allele 8 10 12 13 Quantity 4,000 250 3,000 250 + 250 4,000 + 250 + 3,000 + 250 8 10 12 13 500 = = 6.7% 7,500 Cybergenetics © 2003-2010

Overlapping Alleles Cybergenetics © 2003-2010

Template Average mean variance Cybergenetics © 2003-2010

Template Mixture Weight Probability Distribution mean = 6.7% standard deviation = 0.9% Cybergenetics © 2003-2010

Central Limit Theorem • more data experiments for a template provide greater mixture weight precision • double the precision by doing four times the number of experiments • combine evidence from multiple experiments to obtain a more informative result Cybergenetics © 2003-2010

Probability Solution interacting random variables w | d, g1, g2, … g1 | d, g2, w, … g2 | d, g1, w, … zi | d, g1, g2, w, … find probability distributions by iterative sampling Gelfand, A. and Smith, A. (1990). Sampling based approaches to calculating marginal densities. J. American Statist. Assoc., 85:398-409. Cybergenetics © 2003-2010

Markov Chain Monte Carlo

Prior Probability genotype mixture weight DNA quantity variance parameters

Joint Likelihood Function data pattern variation

Posterior Probability genotype mixture weight data variation

Generally Accepted Method mixture weight genotype James Curran. A MCMC method for resolving two person mixtures. Science & Justice. 2008;48(4):168-77. data variation

Hierarchical Bayesian Model with MCMC Solution • standard approach in modern science • describes uncertainty using probability • the "new calculus" • replaces hard calculus with easy computing • can solve virtually any problem • well-suited to interpreting DNA evidence