% Generated by roxygen2: do not edit by hand % Please edit documentation in R/GxE.test.R \name{GxE.test} \alias{GxE.test} \title{A function to run a test of interaction between a collection of SNPs and exposures (experimental).} \usage{ GxE.test( snp.cols, preprocessed.list, null.mean.vec = c(0, 0), null.sd.vec = c(1, 1), n.permutes = 10000, n.different.snps.weight = 2, n.both.one.weight = 1, weight.function.int = 2 ) } \arguments{ \item{snp.cols}{An integer vector specifying the columns in the input data containing the SNPs to be tested.} \item{preprocessed.list}{The initial list produced by function \code{preprocess.genetic.data}.} \item{null.mean.vec}{A vector of estimated null means for each of the components of the E-GADGETS fitness score. It should be set to the values of the "null.mean" element of the file "null.mean.sd.info.rds" for the observed data, that is saved by the \code{run.gadgets} function.} \item{null.sd.vec}{A vector of estimated null means for each of the components of the E-GADGETS fitness score. It should be set to the values of the "null.se" element of the file "null.mean.sd.info.rds" for the observed data, that is saved by the \code{run.gadgets} function.} \item{n.permutes}{The number of permutations on which to base the test. Defaults to 10000.} \item{n.different.snps.weight}{The number by which the number of different SNPs between a case and complement/unaffected sibling is multiplied in computing the family weights. Defaults to 2.} \item{n.both.one.weight}{The number by which the number of SNPs equal to 1 in both the case and complement/unaffected sibling is multiplied in computing the family weights. Defaults to 1.} \item{weight.function.int}{An integer used to assign family weights. Specifically, we use \code{weight.function.int} in a function that takes the weighted sum of the number of different SNPs and SNPs both equal to one as an argument, denoted as x, and returns a family weight equal to \code{weight.function.int}^x. Defaults to 2.} } \value{ A list of three elements: \describe{ \item{pval}{The p-value of the test.} \item{obs.fitness.score}{The fitness score from the observed data} \item{perm.fitness.scores}{A vector of fitness scores for the permuted datasets.} } } \description{ This function runs a permutation based test run a test of interaction between a collection of SNPs and exposure variables. } \examples{ data(case.gxe) data(dad.gxe) data(mom.gxe) data(exposure) data(snp.annotations.mci) pp.list <- preprocess.genetic.data(case.gxe, father.genetic.data = dad.gxe, mother.genetic.data = mom.gxe, ld.block.vec = rep(6, 4), categorical.exposures = exposure) run.gadgets(pp.list, n.chromosomes = 5, chromosome.size = 3, results.dir = "tmp_gxe", cluster.type = "interactive", registryargs = list(file.dir = "tmp_reg_gxe", seed = 1300), n.islands = 8, island.cluster.size = 4, n.migrations = 1) combined.res <- combine.islands('tmp_gxe', snp.annotations.mci, pp.list, 1) top.snps <- as.vector(t(combined.res[1, 1:3])) set.seed(10) GxE.test.res <- GxE.test(top.snps, pp.list) unlink('tmp_gxe', recursive = TRUE) unlink('tmp_reg_gxe', recursive = TRUE) }