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Figure 1 | BMC Bioinformatics

Figure 1

From: MegaSNPHunter: a learning approach to detect disease predisposition SNPs and high level interactions in genome wide association study

Figure 1

Comparison between MegaSNPHunter and BEAM on synthetic data. Comparison between MegaSNPHunter and BEAM on synthetic data. For each setting, the power is calculated as the proportion of 30 data sets. Each data set contains 2000 samples (1000 cases and 1000 controls) and 1000 SNPs. λ controls the marginal effect. MAF is the minor allele frequency. LD between each unobserved disease locus and the associated marker is measured by r2. (a): The performance comparison on additive model. (b):The performance comparison on multiplicative model.

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BMC Bioinformatics

ISSN: 1471-2105

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