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arXiv · 1307.4956

Computational aspects of DNA mixture analysis

Therese Graversen·Steffen Lauritzen
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Abstract

Statistical analysis of DNA mixtures is known to pose computational challenges due to the enormous state space of possible DNA profiles. We propose a Bayesian network representation for genotypes, allowing computations to be performed locally involving only a few alleles at each step. In addition, we describe a general method for computing the expectation of a product of discrete random variables using auxiliary variables and probability propagation in a Bayesian network, which in combination with the genotype network allows efficient computation of the likelihood function and various other quantities relevant to the inference. Lastly, we introduce a set of diagnostic tools for assessing the adequacy of the model for describing a particular dataset.

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Therese Graversen, Steffen Lauritzen. 2013-07-18. Computational aspects of DNA mixture analysis. https://doi.org/10.1007/s11222-014-9451-7

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