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Fig. 2 | BMC Bioinformatics

Fig. 2

From: SNPxE: SNP-environment interaction pattern identifier

Fig. 2

Examples of SNP-environment interactions using the SNPxE approach. D%: outcome disease prevalence. (n): sample size in each combination. These two patterns were based on \(\mathrm{logit}\left[\mathrm{pr}\left(\mathrm{Y}=1\right)\right]={\beta }_{0}+ {\upbeta }_{4}\mathbf{S}\mathbf{N}\mathbf{P}\times {ENV}_{2vs1}+{\upbeta }_{5}\mathbf{S}\mathbf{N}\mathbf{P}\times {ENV}_{3vs1}\), where Y is the binary disease outcome with a value of 0 or 1 and ENV1 or Env_g3 represent an ordinal environmental factor. Odds ratio1 (OR1) = exp(β4) and OR2 = exp(β5), and the reference group (OR = 1) was the sub-groups inside the frame. a and b are based on simulated data and c and d are based on real data. a overall p-value of the interaction = 7.0 × 10−7; OR1 = 1.5 (95% confidence interval [CI] = 1.2–1.9), p = 3.6 × 10−4; and OR2 = 2.2 (95% CI = 1.5–3.0), p = 1.1 × 10−5. b Overall p-value of the interaction = 3.7 × 10−11; OR1 = 1.8 (95% CI = 1.2–2.7), p = 5.3 × 10−3; and OR2 = 4.3 (95% CI = 2.8–6.6), p = 6.0 × 10−11. c Overall p-value of the interaction = 0.006; OR1 = 0.7 (95% CI = 0.4–1.2), p = 0.209; and OR2 = 2.4 (95% CI = 1.3–4.5), p = 0.004. d Overall p-value of the interaction = 0.0001; OR1 = 1.8 (95% CI = 1.1–3.0), p = 0.012; and OR2 = 2.0 (95% CI = 1.4–3.0), p = 0.004

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