Bayesian Integrative Clustering (iClusterBayes)

Pure R implementation of iClusterBayes for multi-omics clustering.

Performs Bayesian integrative clustering using Gibbs sampling.

Usage

icluster_bayes(
  data_list,
  k,
  n_burnin = 1000,
  n_sample = 2000,
  n_thin = 1,
  prior_alpha = 1,
  prior_sigma = c(1, 1),
  verbose = FALSE
)

Arguments

data_list

List of data matrices (features x samples).

k

Number of clusters.

n_burnin

Number of burn-in iterations (default: 1000).

n_sample

Number of sampling iterations (default: 2000).

n_thin

Thinning interval (default: 1).

prior_alpha

Dirichlet prior parameter (default: 1).

prior_sigma

Prior for residual variance (default: c(1, 1)).

verbose

Print progress.

Value

List with cluster assignments, posterior matrices, and parameters.

References

Mo Q, et al. A fully Bayesian latent variable model for integrative clustering analysis of multi-type omics data. Biostatistics. 2018.

Author

Zaoqu Liu