GenPheno: Generate Phenotypes

Description

Simulate a phenotype based on annotations, covariates, and genotypes.

Usage

GenPheno(
  anno,
  beta,
  covar,
  geno,
  reg_param,
  binary = FALSE,
  include_residual = TRUE,
  indicator = FALSE,
  method = "none",
  prop_causal = 1,
  random_signs = FALSE,
  random_var = 0,
  weights = c(1, 1, 1)
)

Value

(n x 1) numeric vector.

Arguments

anno: (snps x 1) annotation vector.
beta: If method = "none", a (L x 1) coefficient with effect sizes for each annotation category. By default, there are L = 3 annotation categories corresponding to BMVs, DMVs, and PTVs. If method != "none", a scalar effect size for the allelic series burden score.
covar: Covariate matrix.
geno: (n x snps) genotype matrix.
reg_param: Regression parameters.
binary: Generate binary phenotype? Default: FALSE.
include_residual: Include residual? If FALSE, returns the expected value. Intended for testing.
indicator: Convert raw counts to indicators? Default: FALSE.
method: Genotype aggregation method. Default: "none".
prop_causal: Proportion of variants which are causal.
random_signs: Randomize signs? FALSE for burden-type genetic architecture, TRUE for SKAT-type.
random_var: Frailty variance in the case of random signs. Default: 0.
weights: Annotation category weights used for aggregation if method != "none".

Phenotype generation

To generate phenotypes from the baseline model, set method to "none" and provide a vector beta of length equal to the number of annotation categories specifying the effect sizes of each.
To generate phenotypes from the allelic series burden models, set method to "max" or "sum" and provide a scalar beta.
To generate phenotypes from the allelic series SKAT model, set method to "none", set random_signs to true, and provide a vector beta of length equal to the number of annotation categories.