ASKATSS: Allelic Series SKAT-O from Summary Statistics

In AllelicSeries: Allelic Series Test

Allelic Series SKAT-O from Summary Statistics

Description

Allelic series sequence kernel association test from summary statistics.

Usage

ASKATSS(
  anno,
  beta,
  se,
  check = TRUE,
  eps = 1,
  lambda = 1,
  ld = NULL,
  maf = NULL,
  weights = c(1, 2, 3)
)

Arguments

anno	(snps x 1) annotation vector with integer values in 1 through the number of annotation categories L.
beta	(snps x 1) vector of effect sizes for the coding genetic variants within a gene.
se	(snps x 1) vector of standard errors for the effect sizes.
check	Run input checks? Default: TRUE.
eps	Epsilon added to the diagonal of the LD matrix if not positive definite. Note, smaller values increase the chances of a false positive.
lambda	Optional genomic inflation factor. Defaults to 1, which results in no rescaling.
ld	(snps x snps) matrix of correlations among the genetic variants. Although ideally provided, an identity matrix is assumed if not.
maf	(snps x 1) vector of minor allele frequencies. Although ideally provided, defaults to the zero vector.
weights	(L x 1) vector of annotation category weights. Note that the number of annotation categories L is inferred from the length of weights.

Value

Numeric p-value of the allelic series SKAT-O test.

Notes

• The SKAT test requires per-variant minor allele frequencies (MAFs) for the purpose of up-weighting rarer variants. If unknown, maf can be safely omitted. The only consequence is that the SKAT weights will no longer be inversely proportional to the genotypic variance.

Examples

# Generate data.
data <- DGP(n = 1e3)
sumstats <- CalcSumstats(data = data)

# Run allelic series SKAT test from sumstats.
# Note: the SKAT test requires MAF.
results <- ASKATSS(
  anno = sumstats$sumstats$anno,
  beta = sumstats$sumstats$beta, 
  maf = sumstats$sumstats$maf,
  se = sumstats$sumstats$se,
  ld = sumstats$ld
)
show(results)

AllelicSeries documentation built on April 3, 2025, 7:46 p.m.