An information theoretic approach to pedigree reconstruction

Anthony Almudevar

Theoretical Population Biology, 2016, vol. 107, issue C, 52-64

Abstract: Network structure is a dominant feature of many biological systems, both at the cellular level and within natural populations. Advances in genotype and gene expression screening made over the last few decades have permitted the reconstruction of these networks. However, resolution to a single model estimate will generally not be possible, leaving open the question of the appropriate method of formal statistical inference. The nonstandard structure of the problem precludes most traditional statistical methodologies. Alternatively, a Bayesian approach provides a natural methodology for formal inference. Construction of a posterior density on the space of network structures allows formal inference regarding features of network structure using specific marginal posterior distributions.

Keywords: Pedigree reconstruction; Graphical models; Minimum Description Length principle; Bayesian inference (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:eee:thpobi:v:107:y:2016:i:c:p:52-64

DOI: 10.1016/j.tpb.2015.09.006

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