correct_qqplot: A function to draw the corrected quantile-quantile plot for...

In HDMT: A Multiple Testing Procedure for High-Dimensional Mediation Hypotheses

Description

A function to draw the corrected quantile-quantile (Q-Q) plots. The corrected quantiles were computed from the mixture null distribution (green dots) and the naive quantiles were computed from the uniform distribution (red dots).

Usage

correct_qqplot(pmax, pnull, opt="all")

Arguments

pmax	The vector for maximum p-values
pnull	The quantiles of pmax based on the estimated mixture null distribution
opt	Option to draw the plot. opt="all":use all the data points, opt="subset": use a subset of the data points, in case there are too many points in a genome-wide setting, to avoid drawing an overcrowded Q-Q plot with a prohibitive image size.

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)),]

pmax <- apply(input_pvalues,1,max)
nullprop <- null_estimation(input_pvalues)
pnull1 <- adjust_quantile(nullprop$alpha10,nullprop$alpha01,nullprop$alpha00,
                          nullprop$alpha1,nullprop$alpha2,input_pvalues,exact=1)
correct_qqplot(pmax,pnull1)

HDMT documentation built on Jan. 30, 2022, 1:07 a.m.