OINT: Omnibus-INT

Description Usage Arguments Value See Also Examples

View source: R/OINT.R

Description

Association test that synthesizes the DINT and IINT tests. The first approach is most powerful for traits that could have arisen from a rank-preserving transformation of a latent normal trait. The second approach is most powerful for traits that are linear in covariates, yet have skewed or kurtotic residual distributions. During the omnibus test, the direct and indirect tests are separately applied, then the p-values are combined via the Cauchy combination method.

Usage

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OINT(y, G, X = NULL, k = 0.375, simple = FALSE)

Arguments

y

Numeric phenotype vector.

G

Genotype matrix with observations as rows, SNPs as columns.

X

Model matrix of covariates and structure adjustments. Should include an intercept. Omit to perform marginal tests of association.

k

Offset applied during rank-normalization. See RankNorm.

simple

Return the OINT p-values only?

Value

A numeric matrix of p-values, three for each column of G.

See Also

Examples

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set.seed(100)
# Design matrix
X <- cbind(1, rnorm(1e3))
# Genotypes
G <- replicate(1e3, rbinom(n = 1e3, size = 2, prob = 0.25))
storage.mode(G) <- "numeric"
# Phenotype
y <- exp(as.numeric(X %*% c(1, 1)) + rnorm(1e3))
# Omnibus
p <- OINT(y = y, G = G, X = X, simple = TRUE)

Example output



RNOmni documentation built on Oct. 23, 2020, 5:55 p.m.

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