cghFLasso (version 0.2-1)

cghFLasso.ref: A function to process reference CGH arrays using the fused lasso regression

Description

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

Usage

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

Arguments

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.

Value

numeric matrix representing the smoothed result of the reference arrays.

Details

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.

References

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'.

Examples

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")