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Perform MR GxE

Source: R/mrgxe.R
egger_bootstrap.Rd

For a single variant estimated in different sub groups.

Usage

egger_bootstrap(b_gx, se_gx, b_gy, se_gy, nboot = 1000)

Arguments

b_gx

Vector of instrument-exposure associations, one for each sub group

se_gx

Vector of standard errors to b_gx

b_gy

Vector of instrument-outcome associations, one for each sub group

se_gy

Vector of standard errors for b_gy

nboot

Number of bootstraps. Default=1000

Value

List

  • a = intercept estimate (pleiotropy)

  • b = slope estimate (b_iv effect)

  • a_se = standard error of intercept

  • b_se = standard error of slope

  • a_pval = p-value of intercept estimate

  • b_pval = p-value of slope estimate

  • a_mean = mean value of intercept from bootstraps

  • b_mean = mean value of slope estimates from bootstraps

Details

Estimate the degree of pleiotropy using MR GxE. This method uses a negative control type approach based on an assumption that the instrument-exposure association is uncorrelated with the pleiotropic effect. Therefore, as the instrument-exposure association reduces in magnitude, the effect on the outcome will reduce towards an intercept term which represents the pleiotropic effect.

Standard errors are obtained from parametric bootstrap