Usage
blvcm(pheno, geno, model = 3, iter = 30000, burnin = 500, var = -1, lambda = 0.2,
cov = 0, init = c(0,0))
Arguments
pheno
An $N$ x $3$ phenotypic data matrix (trait, family number, zyg=1 for MZ, 2 for DZ), where $N$ is the number of subjects. Please see the example data for more details. For faster convergence, it is recommanded that the phenotype should be standardized.
geno
An $N$ x $K$ genotypic data matrix, where $N$ is the number of subjects and $K$ is the number of rare variants. The value can be 0 or 1. A missing genotype is represented by -9, which will be imputated by BLVCM based on HWE.
model
Twin model: 3 for ACE model, 2 for AE model, 1 for independent subjects
iter
The number of MCMC iterations, which must be positive.
burnin
The number of burn-ins, which must be positive.
var
The variance hyperparameter (must be positive) in the priors for $\beta$ and $\gamma$. If not specified (var=-1), the default value is the variance of the phenotype.
lambda
The threshold $\lambda$ (must be positive) for hypothesis test. The default value is 0.2.
cov
A matrix of other covariates.
init
Initial values for $\beta$ and $\gamma$ (must be non-negative). The default values are 0.