ACGH

Micro-array data for 43 different individuals with a bladder tumor.

datasets

Implements hierarchical procedures to find multiple change-points 
	     through the use of U-statistics. The procedures do not make any 
	     distributional assumptions other than the existence of certain 
	     absolute moments. Both agglomerative and divisive procedures are
	     included. These methods return the set of estimated change-points 
	     as well as other summary information.

Nicholas James

Nonparametric Multiple Change-Point Analysis of Multivariate
        Data

ACGH function

A list with the following components.
  
  data: The micro-array data for 43 individuals. This information is stored in a 2215 by 43 matrix.
  
  individual: A numeric vector indicating which individuals' mico-array data are present.

format

Bleakley K., Vert J.-P. (2011), The group fused Lasso for multiple change-point detection<p></p><p>N. Stransky, C. Vallot, F. Reyal, I. Bernard-Pierrot, S.G. Diez de Mediana, R. Segraves, Y. de Rycke,
P. Elvin, A. Cassidy, C. Sparaggon, A. Graham, j. Southgate, B. Asselain, Y. Allory, C. C. Addou, D. G.
Albertson, J.-P. Thiery, D. K. Chopin, D. Pinkel, and F. Radvanyi. Regional copy number-independent 
deregulation of transcription in cancer. Nat. Genet., 38(12):1386-1396, Dec 2006</p>

ACGH: Bladder Tumor Micro-Array Data

Description

Usage

Arguments

format

source

References

Examples