ofGEM: A meta-analysis approach with filtering for identifying...

In lschen-stat/ofGEM: A Meta-Analysis Approach with Filtering for Identifying Gene-Level Gene-Environment Interactions with Genetic Association Data

Description

This function first conducts a meta-filtering test to filter out unpromising SNPs. It then runs a test of omnibus-filtering-based GxE meta-analysis (ofGEM) that combines the strengths of the fixed- and random-effects meta-analysis with meta-filtering. It can also analyze data from multiple ethnic groups. The p-values are calculated using a sequential sampling approach.

Usage

ofGEM(Z, X, R, weight, threshold = 0.1, maxSim = 1e+06, tol = 10)

Arguments

Z	a matrix of test statistics for gene-environment interactions (GxE) from consortium data. Each row corresponds to a SNP in a set (e.g., a gene), and each column represents a study. For multi-ethnic groups, Z is a list with each element being the matrix for each ethnic group.
X	a matrix of filtering statistics for GxE. Each row corresponds to a SNP in a set, and each column represents a study. For multi-ethnic groups, X is a list with each element being the matrix for each ethnic group.
R	the correlation matrix of test statistics for SNPs in a set. One may use the genotype LD matrix for the set of SNPs to approximate it. This matrix is used when sampling correlated testing and filtering statistics under the null hypothesis and to obtain the null meta-analysis statistics. For multi-ethnic groups, R is a list with each element being the correlation matrix for each ethnic group.
weight	the weight vector for each study, or the weight matrix for each SNP and each study. If the weight is the same across SNPs, it is a vector with length equaling to the number of studies. If the weight is different for different SNPs, it is a matrix with each row corresponding to each SNP and each column representing each study.
threshold	a fixed p-value threshold for filtering test. The default is 0.1.
maxSim	the maximum number of samplings performed in obtaining the sets of correlated testing and filtering statistics under the null. The default is 1e6. This number determines the precision of the p-value calculation.
tol	the tolerance number to stop the sequential sampling procedure. The default is 10. We count the number of sampling-based null meta-statistics that is more extreme than the observed meta-statistics. We sequentially increase the number of sampling with an increment of 100. The sequential sampling will stop if the cumulative count reaches tol. The idea is to stop pursuing a higher precision with more sampling of null if the p-value appears to be not significant. If tol = 0, the number of samplings equals to maxSim.

Value

A list containing

pval_random_mf	the p-value based on the random-effects meta-analysis test with its corresponding meta-filtering.
pval_fixed_mf	the p-value based on the fixed-effects meta-analysis test with its corresponding meta-filtering.
pval_ofGEM	the p-value based on using Fisher's method to aggregating the p-values of fixed- and random-effects meta-analysis tests with meta-filtering
nsim	the number of samplings being performed.

References

Wang, Liu, Pierce, Huo, Olopade, Ahsan, & Chen (2017+). A meta-analysis approach with filtering for identifying gene-level gene-environment interactions with genetic association data. Submitted.

Examples

data(sim_dat)

pval = ofGEM(Z = sim_dat$Z, X = sim_dat$X, R = sim_dat$R, weight = rep(1/6, 6))

lschen-stat/ofGEM documentation built on May 14, 2019, 11:28 a.m.