View source: R/allelic_series_sumstats.R
ASBTSS | R Documentation |
Allelic series burden test from summary statistics.
ASBTSS(
anno,
beta,
se,
check = TRUE,
eps = 1,
lambda = 1,
ld = NULL,
method = "none",
return_beta = FALSE,
weights = c(1, 2, 3)
)
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. |
method |
Method for aggregating across categories: ("none", "sum"). Default: "none". |
return_beta |
Return the estimated effect size? 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 |
If return_beta = TRUE
, a list of including the effect size
data.frame "betas" and the p-value "pval". If return_beta = FALSE
,
a numeric p-value.
The allelic series burden does not require the minor allele frequencies.
# Generate data.
data <- DGP(n = 1e3)
sumstats <- CalcSumstats(data = data)
# Run allelic series burden test from sumstats.
results <- ASBTSS(
anno = sumstats$sumstats$anno,
beta = sumstats$sumstats$beta,
se = sumstats$sumstats$se,
ld = sumstats$ld
)
show(results)
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