cghFLasso.ref: A function to process reference CGH arrays using the fused...
In cghFLasso: Detecting hot spot on CGH array data with fused lasso regression.

Description Usage Arguments Details Value Author(s) References Examples

View source: R/cghFLasso.R

A function to process reference CGH arrays using the fused lasso regression

1	cghFLasso.ref(CGH.Array, chromosome=NULL, filter=NULL)

`CGH.Array`	numeric vector or matrix. It's the result of one or mutiiple CGH experiments. Each column is the log2 ratios returned from one array experiment and is ordered according to the gene/clones' position on the genome. Missing value should be coded as NA.
`chromosome`	numeric vector. Length should be the same as the row number of `CGH.Array`. It's the chromosome number of each gene/clone. If no value is specified, the arrays will be treated as one chromosome.
`filter`	numeric vector. Length should be the same as the row number of `CGH.Array`. Each element takes value 1 or 0. Value 1 means that the corresponding gene/clone will be filter away in ahead of the analysis. If no `filter` is specified, the program will process all the genes/clones in the input arrays.

cghFLasso.ref fits fused lasso regression on reference CGH arrays . The dynamic programming algorithm developed by N.A.Johnson is used for the model fitting.

numeric matrix representing the smoothed result of the reference arrays.

N. A. Johnson, R. Tibshirani and P. Wang

R. Tibshirani, M. Saunders, S. Rosset, J. Zhu and K. Knight (2004) ‘Sparsity and smoothness via the fused lasso’, J. Royal. Statist. Soc. B. (In press), available at http://www-stat.stanford.edu/~tibs/research.html.

P. Wang, Y. Kim, J. Pollack, B. Narasimhan and R. Tibshirani (2005) ‘A method for calling gains and losses in array CGH data’, Biostatistics 2005, 6: 45-58, available at http://www-stat.stanford.edu/~wp57/CGH-Miner/

R. Tibshirani and P. Wang (2007) ‘Spatial smoothing and hot spot detection using the Fused Lasso’, Biostatistics (In press), available at http://www-stat.stanford.edu/~tibs/research.html.

J. Friedman, T. Hastie. R. Tibshirani (2007) ‘Pathwise coordinate optimization and the fused lasso’.

library(cghFLasso)
data(CGH)

#############
### Example 1: Process one chromosome vector without using normal references.

CGH.FL.obj1<-cghFLasso(CGH$GBM.y)
plot(CGH.FL.obj1, index=1, type="Lines")

#############
### Example 2: Process a group of CGH arrays and use normal reference arrays.

Normal.FL<-cghFLasso.ref(CGH$NormalArray,  chromosome=CGH$chromosome)
Disease.FL<-cghFLasso(CGH$DiseaseArray, chromosome=CGH$chromosome, nucleotide.position=CGH$nucposition, FL.norm=Normal.FL, FDR=0.01)

###  Plot for the first arrays
i<-1
plot(Disease.FL, index=i, type="Single")
title(main=paste("Plot for the ", i ,"th BAC array", sep=""))

### Consensus plot
plot(Disease.FL, index=1:4, type="Consensus")
title(main="Consensus Plot for 4 BAC arrays")

### Plot all arrays
plot(Disease.FL, index=1:4, type="All")
title(main="Plot for all 4 arrays")

### Report and output
report<-summary(Disease.FL, index=1:4)
print(report)
output.cghFLasso(report, file="CGH.FL.output.txt")