| SST {MPGE} | R Documentation |
Subset multiple hypothesis testing procedure to combine two steps of testing gene-environment interaction in a two-step procedure.
Description
Run SST to adjust for multiple testing
while combining two steps of the GxE interaction testing procedure. The procedure is applicable for
a multivariate phenotype, as well as a univariate phenotype.
Usage
SST(PVAL, Pg_thr_step1 = 0.005, FWER_step2 = 0.05)
Arguments
PVAL |
A data.frame with three columns.
The first column (PVAL$SNP) provides the name of all SNPs or genetic variants tested.
Second column (PVAL$G.P) contains the p-values of the variants obtained from testing
an overall marginal genetic
association between the multivariate phenotype and each genetic variant individually.
And the third column (PVAL$GE.P) contains the p-values obtained from testing overall GxE effect on the
multivariate phenotype in presence of possible marginal effect due to the genetic variant and
a marginal effect
due to the environmental variable. Number of rows in PVAL is the same as the number
of genetic variants, and it has the same structure as in the output of |
Pg_thr_step1 |
A positive real number between 0 and 1 providing the p-value threshold to select the set of promising SNPs in step 1. These selected SNPs will be tested for GxE effect in the second step. Default is 0.005. |
FWER_step2 |
A positive real number between 0 and 1 specifying the family-wise error rate to be maintained in the second step while identifying the genetic variants having a genome-wide significant overall GxE effect on the multivariate phenotype. Default is 0.05. |
Value
The output is a vector of SNPs identified to have a genome-wide significant overall GxE effect.
References
A Majumdar, KS Burch, S Sankararaman, B Pasaniuc, WJ Gauderman, JS Witte (2020) A two-step approach to testing overall effect of gene-environment interaction for multiple phenotypes. bioRxiv, doi: https://doi.org/10.1101/2020.07.06.190256