epistasis.test: A function to run a test of the null hypothesis that a...

In mnodzenski/epistasisGA: An R package to identify multi-snp effects in nuclear family studies using the GADGETS method

A function to run a test of the null hypothesis that a collection of SNPs do not exhibit epistasis, conditional upon observed marginal SNP-disease associations.

Description

This function runs a permutation based test of the null hypothesis that a collection of SNPs do not exhibit epistasis, conditional upon observed marginal SNP-disease associations.

Usage

epistasis.test(
  snp.cols,
  preprocessed.list,
  n.permutes = 10000,
  n.different.snps.weight = 2,
  n.both.one.weight = 1,
  weight.function.int = 2,
  recessive.ref.prop = 0.75,
  recode.test.stat = 1.64,
  maternal.fetal.test = FALSE
)

Arguments

snp.cols	An integer vector specifying the columns in the input data containing the SNPs to be tested.
preprocessed.list	The initial list produced by function preprocess.genetic.data.
n.permutes	The number of permutations on which to base the test. Defaults to 10000.
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.
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.
weight.function.int	An integer used to assign family weights. Specifically, we use 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 weight.function.int^x. Defaults to 2.
recessive.ref.prop	The proportion to which the observed proportion of informative cases with the provisional risk genotype(s) will be compared to determine whether to recode the SNP as recessive. Defaults to 0.75.
recode.test.stat	For a given SNP, the minimum test statistic required to recode and recompute the fitness score using recessive coding. Defaults to 1.64.
maternal.fetal.test	A boolean indicating whether the test specifically for a maternal-fetal interaction should be run. Defaults to FALSE.

Value

A list of thee elements:

pval

The p-value of the test. (In GADGETS papers, these are instead referred to as h-values)

obs.fitness.score

The fitness score from the observed data

perm.fitness.scores

A vector of fitness scores for the permuted datasets.

Examples

data(case)
data(dad)
data(mom)
data(snp.annotations)

pp.list <- preprocess.genetic.data(as.matrix(case),
                               father.genetic.data = as.matrix(dad),
                               mother.genetic.data = as.matrix(mom),
                               ld.block.vec = rep(25, 4))

run.gadgets(pp.list,
    n.chromosomes = 5, chromosome.size = 3,
    results.dir = "tmp", cluster.type = "interactive",
    registryargs = list(file.dir = "tmp_reg", seed = 1300),
    n.islands = 8, island.cluster.size = 4,
    n.migrations = 2
)

combined.res <- combine.islands("tmp", snp.annotations, pp.list, 2)

top.snps <- as.vector(t(combined.res[1, 1:3]))
set.seed(10)
epi.test.res <- epistasis.test(top.snps, pp.list)

unlink('tmp', recursive = TRUE)
unlink('tmp_reg', recursive = TRUE)

mnodzenski/epistasisGA documentation built on Jan. 17, 2023, 7:07 p.m.