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. 2009 Nov 25;27(3):283–288. doi: 10.1093/imammb/dqp022

The conditional independences between variables derived from two independent identically distributed Markov random fields when pairwise order is ignored

Alun Thomas 1,
PMCID: PMC2948832  PMID: 19942608

Abstract

A result for the equivalence of conditional independence graphs of ordered and unordered vector random variables from first-order Markov models is extended to arbitrary forests. The result is relevant to estimating graphical models for linkage disequilibrium between genetic loci. It explains why, in terms of the conditional independence structure, it sometimes does not matter whether you consider haplotypes or genotypes.

Keywords: graphical modelling, conditional independence graphs, Markov properties, linkage disequilibrium, allelic association

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Footnotes

Funding

National Institutes of Health (R01 GM81417) and U.S. Department of Defense (W81XWH-07-01-0483) to A.T.

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