----------------------------------------------------------- |INSTRUCTIONS FOR USING mBPCR (also for users not used to R)| ----------------------------------------------------------- ##to use the functions of the package## -Open R -Change the working directory with the folder mBPCR. (the user can use the command "file"/"change directory" in the menu of the console, or the command line setwd("path of the folder")). -Type source("mBPCR.R"). ##how to use the help## -All the functions are described in the help in folder html. -To use the help easily, open the file html\00Index.html with a browser. ##examples## -In the help, the description of each function ends with an example of how to use it. -In the folder R-ex, there are the corresponding R scripts. ##attention## Some functions of the package need to know the parameter maxProbeNumber=maximum number of probes that a chromosome (or arm of a chromosome) can have to be analyzed. In fact, the procedure of profile estimation needs the computation of an array of length (length(chromosome)+1)*(length(chromosome)+2)/2. To be sure to set this parameter correctly, try to create the array A <- array(1, dim=(maxProbeNumber+1)*(maxProbeNumber+2)/2), before starting with the estimation procedure ##how to apply mBPCR## -Example 1: ----------- ##import the 10K data of cell line REC ##for windows path <- 'data\\rec10k.dat' ##for linux path <- 'data//rec10k.dat' rec10k <- importCNData(path, NRowSkip=1) ##estimation of the profile of all chromosomes results=estProfileWithMBPCR(path='', sampleName='rec10k', rec10k$snpName, rec10k$chr, rec10k$position, rec10k$logratio, chrToBeAnalyzed=c(1:22,'X'), maxProbeNumber=2000) ##plot the estimated profile of chromosome 3 plotEstProfile(path='', sampleName='rec10k', rec10k$chr, rec10k$position, rec10k$logratio, chrToBePlotted=3, results$estPC, maxProbeNumber=2000) -Example 2 (it could need long time to run): -------------------------------------------- ##import the 250K NSP data of chromosome 11 of cell line JEKO-1 ##for windows path <- 'data\\jekoChr11Array250Knsp.dat' ##for linux ##path <- 'data//jekoChr11Array250Knsp.dat' jekoChr11Array250Knsp <- importCNData(path, NRowSkip=1) ##estimation of the profile of all chromosomes results=estProfileWithMBPCR(path='', sampleName='jeko250Knsp', jekoChr11Array250Knsp$snpName, jekoChr11Array250Knsp$chr, jekoChr11Array250Knsp$position, jekoChr11Array250Knsp$logratio, chrToBeAnalyzed=11, maxProbeNumber=9000, rhoSquare=0.0479, nu=-3.012772e-10, sigmaSquare=0.0699) ##plot the estimated profile of chromosome 3 plotEstProfile(path='', sampleName='jeko250Knsp', jekoChr11Array250Knsp$chr, jekoChr11Array250Knsp$position, jekoChr11Array250Knsp$logratio, chrToBePlotted=11, results$estPC, maxProbeNumber=9000) -Example 3: ----------- ##import the 250K NSP data of chromosome 11 of cell line JEKO-1 ##for windows path <- 'data\\jekoChr11Array250Knsp.dat' ##for linux ##path <- 'data//jekoChr11Array250Knsp.dat' jekoChr11Array250Knsp <- importCNData(path, NRowSkip=1) ## we select a part of chromosome 11 y <- jekoChr11Array250Knsp$logratio[10600:11600] p <- jekoChr11Array250Knsp$position[10600:11600] ##we estimate the profile using the global parameters estimated on the whole genome results <- computeMBPCR(y, nu=-3.012772e-10, rhoSquare=0.0479, sigmaSquare=0.0699, regr=1) plot(p,y) points(p, results$estPC, type='l', col='red') points(p, results$regrCurve, type='l', col='green') ##suggestions## -Even if the goal is to estimate the profile of only a part of the genome, the global parameters should be estimated on the whole genome. -If the goal is to estimate the profile of a patient, it is better to estimate the variance of the segment levels (rhoSquare) on a cell line or on a sample with many aberrations and use this value in the profile estimation of the patient. In fact, we need many aberrations to estimate well rhoSquare.