iBATCGH (version 1.3.1)

Scenario2: Simulated data - Scenario 2

Description

Simulates the data as described in the reference provided below (Scenario 2).

Usage

Scenario2(sigmak = 0.1)

Arguments

sigmak

Standard deviation of the error term

Value

Return a list made of the following items

Y

Matrix of simulated gene expression

X

Matrix of simulated CGH

Xi

True matrix of hidden states

A

Empirical transition matrix

mu

True vector of state specific mean

Sd

True vector of state specific sd

coeff

True matrix of association coefficients between gene expression and CGH probes

distance

Vector of distance between CGH probes

disfix

Length of the chromosome

References

Cassese A, Guindani M, Tadesse M, Falciani F, Vannucci M. A hierarchical Bayesian model for inference of copy number variants and their association to gene expression. Annals of Applied Statistics, 8(1), 148-175. Cassese A, Guindani M, Vannucci M. A Bayesian integrative model for genetical genomics with spatially informed variable selection. Cancer Informatics.

Examples

# NOT RUN {
data <- Scenario2(sigmak = 0.1) 
# }