snp_simuPheno | R Documentation |
Simulate phenotypes using a linear model. When a prevalence is given, the liability threshold is used to convert liabilities to a binary outcome. The genetic and environmental liabilities are scaled such that the variance of the genetic liability is exactly equal to the requested heritability, and the variance of the total liability is equal to 1.
snp_simuPheno(
G,
h2,
M,
K = NULL,
alpha = -1,
ind.row = rows_along(G),
ind.possible = cols_along(G),
prob = NULL,
effects.dist = c("gaussian", "laplace"),
ncores = 1
)
G |
A FBM.code256
(typically |
h2 |
Heritability. |
M |
Number of causal variants. |
K |
Prevalence. Default is |
alpha |
Assumes that the average contribution (e.g. heritability)
of a SNP of frequency |
ind.row |
An optional vector of the row indices (individuals) that
are used. If not specified, all rows are used. |
ind.possible |
Indices of possible causal variants. |
prob |
Vector of probability weights for sampling causal indices.
It can have 0s (discarded) and is automatically scaled to sum to 1.
Default is |
effects.dist |
Distribution of effects.
Either |
ncores |
Number of cores used. Default doesn't use parallelism. You may use nb_cores. |
A list with 3 elements:
$pheno
: vector of phenotypes,
$set
: indices of causal variants,
$effects
: effect sizes (of scaled genotypes) corresponding to set
.
$allelic_effects
: effect sizes, but on the allele scale (0|1|2).
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