DINT | R Documentation |
Applies the rank-based inverse normal transformation (RankNorm
)
to the phenotype y
. Conducts tests of association between the loci in
G
and transformed phenotype, adjusting for the model matrix X
.
DINT(
y,
G,
X = NULL,
k = 0.375,
test = "Score",
ties.method = "average",
simple = FALSE
)
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
|
test |
Either Score or Wald. |
ties.method |
Method of breaking ties, passed to |
simple |
Return the p-values only? |
If simple = TRUE
, returns a vector of p-values, one for each column
of G
. If simple = FALSE
, returns a numeric matrix, including the
Wald or Score statistic, its standard error, the Z-score, and the p-value.
Basic association test BAT
.
Indirect INT test IINT
.
Omnibus INT test OINT
.
set.seed(100)
# Design matrix
X <- cbind(1, stats::rnorm(1e3))
# Genotypes
G <- replicate(1e3, stats::rbinom(n = 1e3, size = 2, prob = 0.25))
storage.mode(G) <- "numeric"
# Phenotype
y <- exp(as.numeric(X %*% c(1, 1)) + stats::rnorm(1e3))
# Association test
p <- DINT(y = y, G = G, X = X)
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