Scenario2: Simulated data - Scenario 2

In iBATCGH: Integrative Bayesian Analysis of Transcriptomic and CGH Data

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

Author(s)

Alberto Cassese

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

data <- Scenario2(sigmak = 0.1) 

iBATCGH documentation built on Oct. 23, 2020, 6:34 p.m.