admix.simulate.quant_pheno_1pop#

admix.simulate.quant_pheno_1pop(geno: Array, hsq: float, n_causal: int | None = None, beta: ndarray | None = None, snp_prior_var: ndarray | None = None, cov: ndarray | None = None, cov_effects: List[float] | None = None, n_sim=10) → dict[source]#

Simulate quantative phenotype for a single population [continuous]

Parameters:

  • geno (da.Array) – (n_snp, n_indiv) array of genotype

  • hsq (float) – Proportion of variance explained by the genotype effects

  • n_causal (int, optional) – number of causal variables, by default None

  • beta (np.ndarray, optional) – Effect sizes

  • snp_prior_var (np.ndarray, optional) – Prior variance of each SNP

  • cov_cols (List[str], optional) – list of covariates to include as covariates, by default None

  • cov_effects (List[float], optional) – list of the effect of each covariate, by default None for each simulation, the cov_effects will be the same

  • n_sim (int, optional) – number of simulations, by default 10

Returns:

  • beta (np.ndarray) – simulated effect sizes (n_snp, n_sim)

  • phe_g (np.ndarray) – simulated genetic component of phenotypes (n_indiv, n_sim)

  • phe (np.ndarray) – simulated phenotype (n_indiv, n_sim)