Identifying Contributors of DNA Mixtures by Means of Quantitative Information of STR Typing

TY - JOUR

T1 - Identifying Contributors of DNA Mixtures by Means of Quantitative Information of STR Typing

AU - Tvedebrink, Torben

AU - Eriksen, Poul Svante

AU - Mogensen, Helle Smidt

AU - Morling, Niels

PY - 2012/7/1

Y1 - 2012/7/1

N2 - Estimating the weight of evidence in forensic genetics is often done in terms of a likelihood ratio, LR. The LR evaluates the probability of the observed evidence under competing hypotheses. Most often, probabilities used in the LR only consider the evidence from the genomic variation identified using polymorphic genetic markers. However, modern typing techniques supply additional quantitative data, which contain very important information about the observed evidence. This is particularly true for cases of DNA mixtures, where more than one individual has contributed to the observed biological stain. This article presents a method for including the quantitative information of short tandem repeat (STR) DNA mixtures in the LR. Also, an efficient algorithmic method for finding the best matching combination of DNA mixture profiles is derived and implemented in an on-line tool for two- and three-person DNA mixtures. Finally, we demonstrate for two-person mixtures how this best matching pair of profiles can be used in estimating the likelihood ratio using importance sampling. The reason for using importance sampling for estimating the likelihood ratio is the often vast number of combinations of profiles needed for the evaluation of the weight of evidence. Online tool is available at http://people.math.aau.dk/ ∼tvede/dna/.

AB - Estimating the weight of evidence in forensic genetics is often done in terms of a likelihood ratio, LR. The LR evaluates the probability of the observed evidence under competing hypotheses. Most often, probabilities used in the LR only consider the evidence from the genomic variation identified using polymorphic genetic markers. However, modern typing techniques supply additional quantitative data, which contain very important information about the observed evidence. This is particularly true for cases of DNA mixtures, where more than one individual has contributed to the observed biological stain. This article presents a method for including the quantitative information of short tandem repeat (STR) DNA mixtures in the LR. Also, an efficient algorithmic method for finding the best matching combination of DNA mixture profiles is derived and implemented in an on-line tool for two- and three-person DNA mixtures. Finally, we demonstrate for two-person mixtures how this best matching pair of profiles can be used in estimating the likelihood ratio using importance sampling. The reason for using importance sampling for estimating the likelihood ratio is the often vast number of combinations of profiles needed for the evaluation of the weight of evidence. Online tool is available at http://people.math.aau.dk/ ∼tvede/dna/.

U2 - 10.1089/cmb.2010.0055

DO - 10.1089/cmb.2010.0055

M3 - Journal article

C2 - 21210742

SN - 1557-8666

VL - 19

SP - 887

EP - 902

JO - Journal of computational biology : a journal of computational molecular cell biology

JF - Journal of computational biology : a journal of computational molecular cell biology

IS - 7

ER -