SMR_interval {iGasso}

Interval Estimates for Summary Data Mendelian Randomization Analysis in the Presence of Winner's Curse

Description

SMR_interval calculates conservative box method interval, k-unit support interval, and Wald confidence interval for the causal effect.

Usage

SMR_interval(
  summary.data,
  sig.level = 5e-08,
  k = 2,
  alpha = 0.05,
  method = "box"
)

Arguments

summary.data

a vector (\hat b_{gx}, se(\hat b_{gx}), \hat b_{gy}, se(\hat b_{gy})) of summary data on the exposure X and the outcome Y. Due to winner's curse, the association p-value between the SNP and the exposure is less than sig.level.

sig.level

the threshold p-value used to select the instrument SNP. The default is 5e-8.

k

the unit used for the k-unit support. The default value is 2.

alpha

(1-\alpha) is the conservative coverage level for the box method interval or the SMR Wald interval. the default value is 0.05

method

method to construct the interval. It is either "support", "box" or "wald". The default is "box".

Value

The returned value is method-dependent.

For method == "box": A list containing the following components:

* an interval estimate.

* type of the interval: completely bounded, exclusive bounded, or bounded.

For method == "support": A list containing the following components:

* Estimate The likelihood estimate of b.

* an interval estimate.

For method == "wald": an interval estimate.

Author(s)

Kai Wang <[e-mail]>

References

Wang, K. (2023) Support interval for two-sample summary data-based mendelia randomization. Genes, 14(1):211.

Wang, K. (2023) Interval estimate of causal effect in summary data based Mendelian randomization in the presence of winner’s curse. Genetic Epidemiology, 14(1):211.

Zhu, Z. et al. (2016) Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nature Genetics, 48(5):481.

Examples

summary.data = c(0.13707, 0.0235162, -0.0637257, 0.013774)
SMR_interval(summary.data)
SMR_interval(summary.data, method = "support")
SMR_interval(summary.data, method = "wald")