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  • Cybergenetics :: DNA Identification Science: The Search for Truth
    Webinars YouTube News Major Projects Newsletters Newsroom Press Releases Trials Contact Directions Information Visiting Support FAQ File Transfer Sending Data Downloads Back to Presentations DNA Identification Science The Search for Truth M W Perlin DNA identification science The search for truth Duquesne University 2010 Summer Research Symposium Keynote Address Pittsburgh PA 30 Jul 2010 Talk PowerPoint presentation with live audio recording of Duquesne University 2010 keynote address Download Handout Download

    Original URL path: http://www.cybgen.com/information/presentations/2010/DUSYM/Perlin_DNA_identification_science_The_search_for_truth/page.shtml (2016-02-12)
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  • Cybergenetics :: Statistical computation for forensic DNA evidence
    Back to Presentations Statistical Computation for Forensic DNA Evidence M W Perlin Statistical computation for forensic DNA evidence University of Pittsburgh Department of Human Genetics Pittsburgh PA 9 Jul 2010 Talk PowerPoint presentation and handout for University of Pittsburgh 2010 talk Download Handout Download PowerPoint Abstract This talk presents the underlying basis for inferring genotypes and match statistics from forensic DNA evidence including mixtures and low template samples We describe

    Original URL path: http://www.cybgen.com/information/presentations/2010/PITTHGEN/Perlin_Statistical_computation_for_forensic_DNA_evidence/page.shtml (2016-02-12)
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  • Cybergenetics :: New York State Subcommittee - May 2010
    File Transfer Sending Data Downloads Back to Presentations New York State Subcommittee May 2010 New York State Division of Criminal Justice Services DNA Subcommittee Meeting New York NY 19 May 2010 Abstract This is the meeting of the New York State Division of Criminal Justice Services DNA Subcommittee on May 19 2010 Talks TrueAllele 174 Genetic Calculator Implementation in the NYSP Crime Laboratory PowerPoint presentation with live audio recording of

    Original URL path: http://www.cybgen.com/information/presentations/2010/NYSDNASUB/Subcommittee2/page.shtml (2016-02-12)
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  • Cybergenetics :: New York State Subcommittee - March 2010
    Criminal Justice Services DNA Subcommittee Meeting New York NY 5 Mar 2010 Abstract This is the meeting of the New York State Division of Criminal Justice Services DNA Subcommittee on March 5 2010 Talks New York State Police TrueAllele 174 Casework developmental validation Powerpoint presentation with live audio recording of Dr Mark Perlin s talk at the New York State DNA Subcommittee Download Handout Download PowerPoint New York State Police

    Original URL path: http://www.cybgen.com/information/presentations/2010/NYSDNASUB/Subcommittee/page.shtml (2016-02-12)
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  • Cybergenetics :: Three Match Statistics, One Verdict
    DNA match statistics in court how to testify on the results of computer based DNA mixture interpretation and why some DNA interpretation methods are more informative than others The presentation will impact the forensic community by enabling practitioners to introduce in court computer based interpretation of DNA evidence that can often provide more informative match results There is currently no consensus on the interpretation of DNA mixtures Some groups advocate inclusion methods while others prefer the likelihood ratio LR Key methodological distinctions include the use of qualitative or quantitative peaks thresholds and computer mixture interpretation These issues all appeared in a recent criminal trial and were integrated in a way that produced a harmonious resolution In 2006 Pennsylvania dentist John Yelenic was brutally murdered in his home State Trooper Kevin Foley boyfriend of the victim s estranged wife was arrested for this crime The major physical evidence was DNA extracted from the victim s fingernails The STR data generated by the FBI laboratory showed a two person mixture largely containing the victim s own DNA along with a 7 unknown second contributor The prosecution presented three different DNA match statistics CPI inclusion statistic of 13 thousand was presented by the FBI The CPI method ignored both the victim profile evident in the data as well as the quantitative peak height information An independent obligate allele interpretation subtraction was done by Dr Cotton Her method did use the victim profile though not the peak heights and produced a match statistic of 23 million The match improvement came from two loci that had four alleles A quantitative computer interpretation addition was reported by Dr Perlin This approach used the victim information together with quantitative peak heights to produce a match statistic of 189 billion The genetic calculator employed a comprehensive scientific model

    Original URL path: http://www.cybgen.com/information/presentations/2010/AAFS/Perlin_Three_match_statistics_one_verdict/page.shtml (2016-02-12)
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  • Cybergenetics :: Casework Validation of Genetic Calculator Mixture Interpretation
    DNA mixture validation studies on interpretation methods that they would like to present in court Interpreting DNA mixtures can be challenging With the advent of statistical computing one can reproducibly infer consistent highly informative results Such reliable mixture inference is critical for the admissibility of scientific evidence This paper establishes the efficacy of computer based genetic calculator mixture interpretation by comparing inferred match information on adjudicated mixture cases relative to currently used manual methods It also demonstrates the reproducibility of the computer s results The key mixture interpretation task is inferring a questioned genotype of an unknown contributor When there is uncertainty in an inferred genotype allele pairs are assigned a probability distribution that describes this uncertainty Different mixture interpretation methods may infer different genotype distributions A genetic calculator provides a statistical computer approach that infers genotypes by hypothesizing all feasible solutions comparing these with observed STR peak height data and assigning higher probabilities to genotype hypotheses that better fit the data We examined two quantitative inference methods TA1 which uses a known victim genotype to help infer the other unknown contributor and TA2 that does not use a victim genotype but instead infers two unknown contributors There are also qualitative list based inclusion methods that apply peak thresholds CLR which uses a known victim genotype and CPI a qualitative approach that does not use a victim genotype The Likelihood Ratio LR is the generally accepted forensic science measure of match rarity The LR gives the probability of a match between the evidence genotype and a suspect relative to a match with a random person The data inferred evidence genotypes above TA1 TA2 CLR CPI each produce a LR match statistic when their probability distribution is substituted into a generic LR match formula The efficacy of the genetic calculator was

    Original URL path: http://www.cybgen.com/information/presentations/2010/AAFS/Perlin_Casework_validation_of_genetic_calculator_mixture_interpretation/page.shtml (2016-02-12)
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  • Cybergenetics :: A match likelihood ratio for DNA comparison
    match probability kinship paternity index and mixtures combined likelihood ratio Recent years have seen the advent of other equally important forensic DNA applications These applications include missing persons familial search low copy number mass disasters touch DNA and complex mixture interpretation Each of these approaches entails the analysis of uncertain DNA data which may include more than one genotype possibility However there is no generally accepted statistical approach that can determine the match rarity for all of these applications The authors have recently developed a general approach to constructing a match likelihood ratio MLR for all such DNA comparison problems 1 The forensic scientist first infers a genetic profile representing genotype uncertainty using probability Then genetic profiles are compared using a straightforward sum of products formula that computes the match likelihood ratio For example the standard Combined Probability of Inclusion CPI mixture statistic can be shown to be a match likelihood ratio Every allele pair that is included in the allele data becomes a genotype possibility each such possibility is then assigned an equal genotype probability The CPI statistic is obtained by substituting these inclusion genotype probabilities into the MLR formula This approach establishes that CPI is indeed a likelihood ratio and also illustrates how genotype probabilities are regularly used in current forensic DNA practice The MLR inference approach is based on Bayesian reasoning Genotype inference is shown to result from the combination of a likelihood function for assessing data and a prior probability Uncertainty in genotype values is represented using probability Any such inferred genotypes can be substituted into the general MLR formula in order to obtain a rigorous likelihood ratio statistic that describe the rarity of genotype match Inferring genotypes and then comparing them in a general match likelihood ratio can be helpful in i performing objective unbiased

    Original URL path: http://www.cybgen.com/information/presentations/2009/AAFS/Perlin_Kadane_Cotton_A_match_likelihood_ratio_for_DNA_comparison/page.shtml (2016-02-12)
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  • Cybergenetics :: Identifying victim remains from uncertain data
    in the context of the World Trade Center WTC STR data At the DNA level VR samples are often degraded mixed burned contain minimal DNA or are compromised in other ways PE samples are collected from contaminated environments and may include mixed or degraded DNA With FR samples there can be uncertainty in the family kinship relationships Human visual review of the STR data is needed to determine which data are good mixed or unusable Indeed the STR lanes or injections associated with a particular sample may be derived from different individuals To disambiguate the data we use a Visual User Interface VUIer tool that lets an analyst view all of the provided lanes for a given sample and then group compatible lanes together to form one or more TrueAllele genetic calculation requests for computer interpretation of that sample In our WTC workflow a VUIer operator can inspect data and generate interpretation requests for 30 VR samples every hour When inferring a profile from uncertain mass disaster data the resulting DNA profile may include more than one genotype This profile uncertainty can be represented by assigning probabilities to genotypes 1 The forensic analyst can use the TrueAllele genetic calculator to infer genotypes in many common scenarios For example the calculator can infer profiles from mixtures having two unknown contributors statistically combine uncertain data from multiple lanes and infer a missing person s profile from kinship data To compare victim remains profiles with missing person profiles the TrueAllele matching module computes a likelihood ratio that compares the probability of a victim remains match with a missing person to that with a random person 1 Every match comparison in the system whether kinship or STR has a numeric likelihood ratio score that measures the degree of DNA identity To help the forensic

    Original URL path: http://www.cybgen.com/information/presentations/2009/AAFS/Perlin_Sinelnikov_Vey_Legler_Clarke_Identifying_victim_remains_from_uncertain_data/page.shtml (2016-02-12)
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