InferenceXi: Postprocessing - Inference on the latent states

In iBATCGH: Integrative Bayesian Analysis of Transcriptomic and CGH Data

Description

This function returns the modal latent states.

Usage

InferenceXi(listXi, niter, burnin)

Arguments

listXi	Last three objects of the output of the main function
niter	Number of Monte Carlo Markov Chain iterations
burnin	Burn-in

Details

Must use the same burn-in as in the main function.

Value

Matrix of modal latent states, i.e. estimated Copy Number Variants. A four class classification is considered:

1. Loss

2. Neutral

3. Gain

4. Amplification

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.

See Also

See Also as Inference

Examples

##See Inference

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