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Figure 6 | BMC Bioinformatics

Figure 6

From: A hierarchical Bayesian network approach for linkage disequilibrium modeling and data-dimensionality reduction prior to genome-wide association studies

Figure 6

Directed acyclic graph of the FHLC model learned for haplotypes (phased genotypes) of Daly et al .'s dataset. The light shade indicates the observed variables whereas the dark shade points out the latent variables. Observed variables are numbered from 1 to 103 whereas latent variables are denoted "Hℓ_i" where ℓ specifies the layer number and i enumerates the different variables belonging to a same layer. We recall that in any FHLCM graph, edges are directed from top to bottom. a = 0.2, b = 2, card max = 20, t CAST = 0.95, t MI = quantile MI (0.95), t = 0.3 (for CFHLC parameter description, see Section Algorithm).

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BMC Bioinformatics

ISSN: 1471-2105

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