output.cghFLasso {cghFLasso} | R Documentation |
Output gain/loss calls by cghFLasso.
output.cghFLasso(summary.obj, file, gene.info=NULL)
summary.obj |
an object of class summary.cghFLasso , usually, a result of a call to summary.cghFLasso . |
file |
a character specifying the file name to output the data. |
gene.info |
matrix. Additional gene/clone annotation to output. |
Output gain/loss calls by cghFLasso.
No return value.
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")