AllelicSeries (version 0.1.1.5)

COASTSS: COding-variant Allelic Series Test from Summary Statistics

Description

Main function for performing the allelic series test from summary statistics. Performs both Burden and SKAT type tests, then combines the results to calculate an omnibus p-value. Note that not all tests included in COAST are available when working with summary statistics.

Usage

COASTSS(
  anno,
  beta,
  se,
  check = TRUE,
  eps = 1,
  lambda = c(1, 1, 1),
  ld = NULL,
  maf = NULL,
  pval_weights = c(0.25, 0.25, 0.5),
  weights = c(1, 2, 3)
)

Value

Numeric p-value.

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, epsilon should increase as the sample size decreases.

lambda

Optional (3 x 1) vector of inflation factors, one for each component test. Defaults to a 1s vector, 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.

pval_weights

(3 x 1) vector of relative weights for combining the component tests to perform the omnibus test. The default of c(0.25, 0.25, 0.50) gives the SKAT test equal weight to the two burden tests.

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)
sumstats <- CalcSumstats(data = data)

# Run the Coding-variant Allelic Series Test from summary statistics.
results <- COASTSS(
  anno = sumstats$sumstats$anno,
  beta = sumstats$sumstats$beta, 
  se = sumstats$sumstats$se,
  ld = sumstats$ld,
  maf = sumstats$sumstats$maf,
)
show(results)