AllelicSeries (version 0.1.1.5)

ASKAT: Allelic Series SKAT Test

Description

Sequence kernel association test (SKAT) with allelic series weights.

Usage

ASKAT(
  anno,
  geno,
  pheno,
  apply_int = TRUE,
  covar = NULL,
  is_pheno_binary = FALSE,
  min_mac = 0,
  return_null_model = FALSE,
  weights = c(1, 2, 3)
)

Value

If return_null_model, a list containing the p-value and the SKAT null model. Otherwise, a numeric p-value.

Arguments

anno

(snps x 1) annotation vector with integer values in 1 through the number of annotation categories L.

geno

(n x snps) genotype matrix.

pheno

(n x 1) phenotype vector.

apply_int

Apply rank-based inverse normal transform to the phenotype? Default: TRUE. Ignored if phenotype is binary.

covar

(n x p) covariate matrix. Defaults to an (n x 1) intercept.

is_pheno_binary

Is the phenotype binary? Default: FALSE.

min_mac

Minimum minor allele count for inclusion. Default: 0.

return_null_model

Return the null model in addition to the p-value? Useful if running additional SKAT tests. Default: FALSE.

weights

(L x 1) vector of annotation category weights. Note that the number of annotation categories L is inferred from the length of weights.

Examples

# Generate data.
data <- DGP(n = 1e3, snps = 1e2)

# Run the Allelic Series SKAT Test.
# Note: the output is a scalar p-value.
results <- ASKAT(
  anno = data$anno,
  geno = data$geno,
  pheno = data$pheno,
  covar = data$covar
)