dat {Bayenet}

simulated data for demonstrating the features of Bayenet.

Description

Simulated gene expression data for demonstrating the features of Bayenet.

Usage

data("dat")

Format

dat consists of four components: X, Y, clin, coef.

Details

The data model for generating Y

Use subscript i to denote the ith subject. Let (Y_{i}, X_{i}, clin_{i}) (i=1,\ldots,n) be independent and identically distributed random vectors. Y_{i} is a continuous response variable representing the cancer outcome and disease phenotype. X_{i} is the p–dimensional vector of genetic factors. The clinical factors is denoted as the q-dimensional vector clin_{i}. The \epsilon follows some heavy-tailed distribution. Considering the following model:

Y_{i} = \alpha_{0} + \sum_{k=1}^{q}\gamma_{k}C_{ik}+\sum_{j=1}^{p}\beta_{j}X_{ij}+\epsilon_{i},

where \alpha_{0} is the intercept, \gamma_{k}'s and \beta_{j}'s are the regression coefficients corresponding to effects of clinical factors and genetic variants, respectively. Denote \gamma=(\gamma_{1}, \ldots, \gamma_{q})^{T}, \beta=(\beta_{1}, \ldots, \beta_{p})^{T}. Then model can be written as

Y_{i} = C_{i}\gamma + X_{i}\beta + \epsilon_{i}.

See Also

Bayenet

Examples

data(dat)
dim(X)