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iClusterPlus (version 1.8.0)

iClusterPlus: Integrative clustering of multiple genomic data types

Description

Given multiple genomic data types (e.g., copy number, gene expression, DNA methylation) measured in the same set of samples, iClusterPlus fits a regularized latent variable model based clustering that generates an integrated cluster assignment based on joint inference across data types

Usage

iClusterPlus(dt1,dt2=NULL,dt3=NULL,dt4=NULL,
	type=c("gaussian","binomial","poisson","multinomial"),
 	K=2,alpha=c(1,1,1,1),lambda=c(0.03,0.03,0.03,0.03),
	n.burnin=100,n.draw=200,maxiter=20,sdev=0.05,eps=1.0e-4)

Arguments

dt1
A data matrix. The rows represent samples, and the columns represent genomic features.
dt2
A data matrix. The rows represent samples, and the columns represent genomic features.
dt3
A data matrix. The rows represent samples, and the columns represent genomic features.
dt4
A data matrix. The rows represent samples, and the columns represent genomic features.
type
Data type, which can be gaussian, binomial, poisson, multinomial.
K
The number of eigen features. Given K, the number of cluster is K+1.
alpha
Vector of elasticnet penalty terms. At this version of iClusterPlus, elasticnet is not used. Therefore, all the elements of alpha are set to 1.
lambda
Vector of lasso penalty terms.
n.burnin
Number of MCMC burnin.
n.draw
Number of MCMC draw.
maxiter
Maximum iteration for the EM algorithm.
sdev
standard deviation of random walk proposal.
eps
Algorithm convergence criterion.

Value

  • A list with the following elements.
  • alphaIntercept parameter.
  • betaInformation parameter.
  • clustersCluster assignment.
  • centersCluster center.
  • meanZLatent variable.
  • BICBayesian information criterion.
  • dev.ratiosee dev.ratio defined in glmnet package.
  • difabsolute difference for the parameters in the last and next-to-last iterations.

References

Qianxing Mo, Sijian Wang, Venkatraman E. Seshan, Adam B. Olshen, Nikolaus Schultz, Chris Sander, R. Scott Powers, Marc Ladanyi, and Ronglai Shen. (2013). Pattern discovery and cancer gene identification in integrated cancer genomic data. Proc. Natl. Acad. Sci. USA. 110(11):4245-50.

See Also

plotiCluster,iCluster, compute.pod

Examples

Run this code
# see iManual.pdf

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