fdr_est {HDMT} | R Documentation |
A function to compute the estimated pointwise FDR for every observed p-max
Description
A function to compute the estimated pointwise FDR based on the proposed joint significance mixture null method (JS-mixture).
Usage
fdr_est(alpha00, alpha01, alpha10, alpha1, alpha2, input_pvalues, exact = 0)
Arguments
alpha00 |
A numeric number represents the proportion of null |
alpha01 |
A numeric number represents the proportion of null |
alpha10 |
A numeric number represents the proportion of null |
alpha1 |
A numeric number represents the proportion of null alpha=0 |
alpha2 |
A numeric number represents the proportion of null beta=0 |
input_pvalues |
A matrix contains two columns of p-values for candidate mediators. Column 1 is the p-value of testing if an exposure is associated with the mediator (alpha!=0). Column 2 is the p-value of testing if a mediator is associated with the outcome adjusted for the exposure (beta!=0) |
exact |
The option to choose from two methods. exact=0: approximation without estimating the CDFs; exact=1: estimate the CDFs nonparametrically |
Details
A function to estimate the pointwise FDR based on the proposed method to estimate the mixture null distribution. See Dai et al (2020) for details of how to compute quantiles using the approximation method (exact=0) or the exact method (exact=1).
Value
The estimated pointwise FDR for p-max
Author(s)
James Y. Dai and X. Wang
References
James Y. Dai, Janet L. Stanford, Michael LeBlanc. A multiple-testing procedure for high-dimensional mediation hypotheses, Journal of the American Statistical Association, 2020, DOI: 10.1080/01621459.2020.1765785.
Examples
data(snp_input)
input_pvalues <- snp_input
#To save time for illustration, we use 10 percent of rows
input_pvalues <- input_pvalues[sample(1:nrow(input_pvalues),size=ceiling(nrow(input_pvalues)/10)),]
nullprop <- null_estimation(input_pvalues)
fdr <- fdr_est(nullprop$alpha00,nullprop$alpha01,nullprop$alpha10,
nullprop$alpha1,nullprop$alpha2,input_pvalues,exact=0)