| clac.PlotSingleArray.R {clac} | R Documentation |
A function to plot one single array for CLAC result.
clac.PlotSingleArray.R(i, NormalResult, clac.result, centromere=NULL, graylevel=0.9)
i |
integer specifying which array to plot |
NormalResult |
result object of function clac.preparenormal.R |
clac.result |
result object of function clac.tumorarray.R |
centromere |
numeric vector specifying the centromere positions. If missing, the default centromere value of human genome will be used. |
graylevel |
numeric value between 0 and 1, specifying the gray level for the background scale lines. 0 for black and 1 for white. |
clac.PlotSingleArray.R plot one single array for CLAC result.
No return value.
Pei Wang
P. Wang, Y. Kim, J. Pollack, B. Narasimhan and R. Tibshirani, ¡°A method for calling gains and losses in array CGH data¡±, Biostatistics (accepted for publication 4/5/2004), available at http://www-stat.stanford.edu/~wp57/CGH-Miner/
library(clac)
data(BACarray)
attach(BACarray)
############ prepare the normal reference arrays
NormalResult<-clac.preparenormal.R(DiseaseArray, NormalArray, Normal.Type=rep(0,3), chromosome.number=chromosome, nucleotide.position=nucposition, windowsize=5, targetFDR=0.01, chromosomeOption=FALSE)
############ clac on selected tumor arrays
clac.result<-clac.tumorarray.R(NormalResult, tumorarrayIndex=1:4)
############ Plot for the first arrays
i<-1
clac.PlotSingleArray.R(i, NormalResult, clac.result)
title(main=paste("CLAC Plot for the ", i ,"th BAC array; FDR=", round(clac.result$fdr[i],3), sep=""))
############ consensus plot
clac.PlotConsensus.R(clac.result, chromosome, nucposition, 1:4)
title(main="Consensus Plot for 4 BAC arrays")
############ Plot all arrays
clac.PlotAllArray.R(NormalResult, clac.result)
title(main="Plot for all 4 arrays")