archive-com.com » COM » C » CYBGEN.COM

Total: 359

Choose link from "Titles, links and description words view":

Or switch to "Titles and links view".
  • Cybergenetics :: Establishing the Limits of TrueAllele Casework: A Validation Study
    as a webinar on December 4th 2013 Abstract The limits of the expert system TrueAllele Casework TA were explored using challenging mock casework profiles that included 17 single source and 18 two 15 three and 7 four person DNA mixtures The sensitivity ability to detect a minor contributor of the TA analysis process was examined by challenging the system with mixture DNA samples that exhibited allelic and locus drop out

    Original URL path: http://www.cybgen.com/information/publication/2015/JFS/Greenspoon-Schiermeier-Wood-Jenkins-Establishing-the-limits-of-TrueAllele-Casework-a-validation-study/page.shtml (2016-02-12)
    Open archived version from archive


  • Cybergenetics :: TrueAllele Genotype Identification on DNA Mixtures Containing up to Five Unknown Contributors
    at the 66th Annual Scientific Meeting of the American Academy of Forensic Sciences in Seattle WA in February of 2014 Abstract Computer methods have been developed for mathematically interpreting mixed and low template DNA The genotype modeling approach computationally separates out the contributors to a mixture with uncertainty represented through probability Comparison of inferred genotypes calculates a likelihood ratio LR which measures identification information This study statistically examined the genotype

    Original URL path: http://www.cybgen.com/information/publication/2014/JFS/Perlin-Hornyak-Sugimoto-Miller-TrueAllele-genotype-identification-on-DNA-mixtures-containing-up-to-five-unknown-contributors/page.shtml (2016-02-12)
    Open archived version from archive

  • Cybergenetics :: TrueAllele Casework on Virginia DNA Mixture Evidence: Computer and Manual Interpretation in 72 Reported Criminal Cases
    a commonly encountered form of biological evidence that contain DNA from two or more contributors Laboratory analysis of mixtures produces data signals that usually cannot be separated into distinct contributor genotypes Computer modeling can resolve the genotypes up to probability reflecting the uncertainty inherent in the data Human analysts address the problem by simplifying the quantitative data in a threshold process that discards considerable identification information Elevated stochastic threshold levels potentially discard more information This study examines three different mixture interpretation methods In 72 criminal cases 111 genotype comparisons were made between 92 mixture items and relevant reference samples TrueAllele computer modeling was done on all the evidence samples and documented in DNA match reports that were provided as evidence for each case Threshold based Combined Probability of Inclusion CPI and stochastically modified CPI mCPI analyses were performed as well TrueAllele s identification information in 101 positive matches was used to assess the reliability of its modeling approach Comparison was made with 81 CPI and 53 mCPI DNA match statistics that were manually derived from the same data There were statistically significant differences between the DNA interpretation methods TrueAllele gave an average match statistic of 113 billion CPI averaged 6

    Original URL path: http://www.cybgen.com/information/publication/2014/PLoSONE/Perlin-Dormer-Hornyak-Schiermeier-Wood-Greenspoon-TrueAllele-Casework-on-Virginia-DNA-Mixture-Evidence/page.shtml (2016-02-12)
    Open archived version from archive

  • Cybergenetics :: New York State TrueAllele® Casework Validation Study
    of Forensic Sciences Abstract DNA evidence can pose interpretation challenges particularly with low level or mixed samples It would be desirable to make full use of the quantitative data consider every genotype possibility and objectively produce accurate and reproducible DNA match results Probabilistic genotype computing is designed to achieve these goals This validation study assessed TrueAllele 174 probabilistic computer interpretation on 368 evidence items in 41 test cases and compared

    Original URL path: http://www.cybgen.com/information/publication/2013/JFS/Perlin-Belrose-Duceman-New-York-State-TrueAllele-Casework-validation-study/page.shtml (2016-02-12)
    Open archived version from archive

  • Cybergenetics :: DNA mixture genotyping by probabilistic computer interpretation of binomially-sampled laser captured cell populations: combining quantitative data for greater identification information
    criminal cases and their interpretation can be challenging particularly if the amount of DNA contributed by both individuals is approximately equal Due to an inevitable degree of uncertainty in the constituent genotypes reduced statistical weight is given to the mixture evidence compared to that expected from the constituent single source contributors The ultimate goal of mixture analysis then is to precisely discern the constituent genotypes and here we posit a novel strategy to accomplish this We hypothesised that LCM mediated isolation of multiple groups of cells binomial sampling from the admixture would create separate cell sub populations with differing constituent weight ratios Furthermore we predicted that interpreting the resulting DNA profiling data by the quantitative computer based TrueAllele 174 interpretation system would result in an efficient recovery of the constituent genotypes due to newfound abilities to compute a maximum LR from sub samples with skewed weight ratios and to jointly interpret all possible pairings of sub samples using a joint likelihood function As a proof of concept 10 separate cell samplings of size 20 recovered by LCM from each of two 1 1 buccal cell mixtures were DNA STR profiled using a specifically developed LCN methodology with the data analyzed

    Original URL path: http://www.cybgen.com/information/publication/2012/SJ/Ballantyne-Hanson-Perlin-DNA-mixture-genotyping-by-probabilistic-computer-interpretation-of-binomially-sampled-laser-captured-cell-populations-combining-quantitative-data-for-greater-identification-information/page.shtml (2016-02-12)
    Open archived version from archive

  • Cybergenetics :: When Good DNA Goes Bad
    2013 Downloads Download Full Article Journal of Forensic Research Abstract DNA evidence is the forensic gold standard However the interpretation of this evidence can be challenging Sophisticated mathematical computing can provide accurate and reliable interpretation of DNA mixtures that contain two or more individuals But the reliability of human review of such data is less well established This paper explores what happens when good DNA data is badly interpreted The

    Original URL path: http://www.cybgen.com/information/publication/2013/JFR/Perlin-When-good-DNA-goes-bad/page.shtml (2016-02-12)
    Open archived version from archive

  • Cybergenetics :: An Information Gap in DNA Evidence Interpretation
    ONE Abstract Forensic DNA evidence often contains mixtures of multiple contributors or is present in low copy numbers The resulting data signals may appear to be relatively uninformative when interpreted using qualitative inclusion based methods However these same data can yield greater identification information when interpreted by computer using quantitative data modeling methods This study applies both qualitative and quantitative interpretation methods to a well characterized DNA mixture and dilution

    Original URL path: http://www.cybgen.com/information/publication/2009/PLoSONE/Perlin-Sinelnikov-An-information-gap-in-DNA-evidence-interpretation/page.shtml (2016-02-12)
    Open archived version from archive

  • Cybergenetics :: Match Likelihood Ratio for Uncertain Genotypes
    Article Abstract Genetic data are not necessarily fully informative leading to uncertainty in an inferred genotype The posterior genotype probability distribution incorporates the identification information present in the data To compare uncertain genotypes we introduce here a match likelihood ratio MLR a simple generalization of the likelihood ratio standardly used to understand the import of genetic evidence in forensic applications The MLR gives the relative probability of a match between

    Original URL path: http://www.cybgen.com/information/publication/2009/LPR/Perlin-Kadane-Cotton-Match-likelihood-ratio-for-uncertain-genotypes/page.shtml (2016-02-12)
    Open archived version from archive