This paper presents a coherent probabilistic framework for taking account of allelic dropout, stutter bands and silent alleles when interpreting STR DNA profiles from a mixture sample using peak size information arising from a PCR analysis. This information can be exploited for evaluating the evidential strength for a hypothesis that DNA from a particular person is present in the mixture. It extends an earlier Bayesian network approach that ignored such artifacts. We illustrate the use of the extended network on a published casework example.
COWELL R., G., LAURITZEN S., L., Mortera, J. (2011). Probabilistic Expert Systems for Handling Artifacts in Complex DNA Mixtures. FORENSIC SCIENCE INTERNATIONAL: GENETICS, 5, 202-209 [10.1016/j.fsigen.2010.03.008].
Probabilistic Expert Systems for Handling Artifacts in Complex DNA Mixtures
MORTERA, Julia
2011-01-01
Abstract
This paper presents a coherent probabilistic framework for taking account of allelic dropout, stutter bands and silent alleles when interpreting STR DNA profiles from a mixture sample using peak size information arising from a PCR analysis. This information can be exploited for evaluating the evidential strength for a hypothesis that DNA from a particular person is present in the mixture. It extends an earlier Bayesian network approach that ignored such artifacts. We illustrate the use of the extended network on a published casework example.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
