assocTestSingle: Genotype Association Testing with Mixed Models

Description Usage Arguments Details Value Author(s) See Also Examples

Description

assocTestSingle performs genotype association tests using the null model fit with fitNullModel.

Usage

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## S4 method for signature 'SeqVarIterator'
assocTestSingle(gdsobj, null.model, test=c("Score", "Wald"),
                GxE=NULL, verbose=TRUE)

Arguments

gdsobj

An object of class SeqVarIterator from the package SeqVarTools containing the genotype data for the variants and samples to be used for the analysis.

null.model

A null model object returned by fitNullModel.

test

A character string specifying the type of test to be performed. The possibilities are "Score" (default) or "Wald"; only "Score" can be used when the family of the null model fit with fitNullModel is not gaussian.

GxE

A vector of character strings specifying the names of the variables for which a genotype interaction term should be included. If NULL (default) no genotype interactions are included. See 'Details' for further information.

verbose

Logical indicator of whether updates from the function should be printed to the console; the default is TRUE.

Details

Sporadic missing genotype values are mean imputed using the minor allele frequency (MAF) calculated on all other samples at that variant.

The input GxE can be used to perform GxE tests. Multiple interaction variables may be specified, but all interaction variables specified must have been included as covariates in fitting the null model with fitNullModel. When performing GxE analyses, assocTestSingle will report two tests: (1) the joint test of all genotype interaction terms in the model (this is the test for any genotype interaction effect), and (2) the joint test of the genotype term along with all of the genotype interaction terms (this is the test for any genetic effect). Individual genotype interaction terms can be tested by creating Wald test statistics from the reported effect size estimates and their standard errors (Note: when GxE contains a single continuous or binary covariate, this test is the same as the test for any genotype interaction effect mentioned above).

Value

A data.frame where each row refers to a different variant with the columns:

variant.id

The variant ID

chr

The chromosome value

pos

The base pair position

allele.index

The index of the alternate allele. For biallelic variants, this will always be 1.

n.obs

The number of samples with non-missing genotypes

freq

The estimated alternate allele frequency

If test is "Score":

Score

The value of the score function

Score.SE

The estimated standard error of the Score

Score.Stat

The score Z test statistic

Score.pval

The score p-value

If test is "Wald" and GxE is NULL:

Est

The effect size estimate for each additional copy of the alternate allele

Est.SE

The estimated standard error of the effect size estimate

Wald.Stat

The Wald Z test statistic

Wald.pval

The Wald p-value

If test is "Wald" and GxE is not NULL:

Est.G

The effect size estimate for the genotype term

Est.G:env

The effect size estimate for the genotype*env interaction term. There will be as many of these terms as there are interaction variables, and "env" will be replaced with the variable name.

SE.G

The estimated standard error of the genotype term effect size estimate

SE.G:env

The estimated standard error of the genotype*env effect size estimate. There will be as many of these terms as there are interaction variables, and "env" will be replaced with the variable name.

GxE.Stat

The Wald Z test statistic for the test of all genotype interaction terms. When there is only one genotype interaction term, this is the test statistic for that term.

GxE.pval

The Wald p-value for the test of all genotype interaction terms; i.e. the test of any genotype interaction effect

Joint.Stat

The Wald Z test statistic for the joint test of the genotype term and all of the genotype interaction terms

Joint.pval

The Wald p-value for the joint test of the genotype term and all of the genotype interaction terms; i.e. the test of any genotype effect

The effect size estimate is for each copy of the alternate allele. For multiallelic variants, each alternate allele is tested separately.

Author(s)

Matthew P. Conomos, Stephanie M. Gogarten, Tamar Sofer, Ken Rice, Chaoyu Yu

See Also

fitNullModel for fitting the null mixed model needed as input to assocTestSingle. SeqVarIterator for creating the input object with genotypes.

Examples

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library(SeqVarTools)
library(Biobase)

# open a sequencing GDS file
gdsfile <- seqExampleFileName("gds")
gds <- seqOpen(gdsfile)

# simulate some phenotype data
data(pedigree)
pedigree <- pedigree[match(seqGetData(gds, "sample.id"), pedigree$sample.id),]
pedigree$outcome <- rnorm(nrow(pedigree))

# construct a SeqVarIterator object
seqData <- SeqVarData(gds, sampleData=AnnotatedDataFrame(pedigree))
iterator <- SeqVarBlockIterator(seqData)

# fit the null model
nullmod <- fitNullModel(iterator, outcome="outcome", covars="sex")

# run the association test
assoc <- assocTestSingle(iterator, nullmod)

seqClose(iterator)

GENESIS documentation built on Aug. 3, 2018, 6 p.m.