% 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)

 
 }