estProfileWithMBPCRforOligoSnpSet {mBPCR} | R Documentation |
Function to estimate the copy number profile with a piecewise constant function using mBPCR. Eventually, it is possible to estimate the profile with a
smoothing curve, using either the Bayesian Regression Curve with K_2 (BRC with K_2) or the Bayesian Regression Curve Averaging over k (BRCAk). It is also possible
to choose the estimator of the variance of the levels rhoSquare
(i.e. either \hat{ρ}_1^2 or \hat{ρ}^2) and by default \hat{ρ}_1^2 is used.
estProfileWithMBPCRforOligoSnpSet(sampleData, sampleToBeAnalyzed, chrToBeAnalyzed, maxProbeNumber, ifLogRatio=1, rhoSquare=NULL, kMax=50, nu=NULL, sigmaSquare=NULL, typeEstRho=1, regr=NULL)
sampleData |
object of type oligoSnpSet. The following fields must not be empty: |
sampleToBeAnalyzed |
vector containing the number of the columns corresponding to the samples the user wants to analyze. |
chrToBeAnalyzed |
array containing the name of the chromosomes that the user wants to analyze. The possible values of the chromosomes are: the integers from 1 to 22, 'X' and 'Y'. |
maxProbeNumber |
maximum number of probes that a chromosome (or arm of a chromosome) can have to be analyzed. The procedure of profile estimation
needs the computation of an array of length (length(chromosome)+1)*(length(chromosome)+2)/2. To be sure to have set this parameter
correctly, try to create the array |
ifLogRatio |
denotes whether the original log2 data were centered at zero (i.e. they were in log2ratio scale) or not. By default, they are considered as derived by log2ratio data ( |
rhoSquare |
variance of the segment levels. If |
kMax |
maximum number of segments |
nu |
mean of the segment levels. If |
sigmaSquare |
variance of the noise. If |
typeEstRho |
choice of the estimator of |
regr |
choice of the computation of the regression curve. If |
By default, the function estimates the copy number profile with mBPCR and estimating rhoSquare on the sample, using \hat{ρ}_1^2. It is
also possible to use \hat{ρ}^2 as estimator of rhoSquare
, by setting typeEstRho=0
, or to directly set the value of the parameter.
The function gives also the possibility to estimate the profile with a Bayesian regression curve: if regr="BRC"
the Bayesian Regression Curve with K_2 is computed (BRC with K_2), if regr="BRCAk"
the Bayesian
Regression Curve Averaging over k is computed (BRCAk).
A list containing:
estPC |
an oligoSnpSet equal to sampleData apart from the field |
regrCurve |
an oligoSnpSet equal to sampleData apart from the field |
The matrices assayData(estPC)$copyNumber
and assayData(regrCurve)$copyNumber
have the same dimension of assayData(sampleData)$copyNumber
, hence their elements,
corresponding to the not analyzed chromosomes and samples, are equal to NA
.
Rancoita, P. M. V., Hutter, M., Bertoni, F., Kwee, I. (2009). Bayesian DNA copy number analysis. BMC Bioinformatics 10: 10. http://www.idsia.ch/~paola/mBPCR
estProfileWithMBPCR
, computeMBPCR
###import an example of oligoSnpSet data #data(oligoSetExample, package="oligoClasses") ##estimation of chromosome 2 in sample 1 #r <-estProfileWithMBPCRforOligoSnpSet(oligoSet, sampleToBeAnalyzed=1, chrToBeAnalyzed=2, maxProbeNumber=1000, ifLogRatio=0, rhoSquare=0.0889637) ##plot of the estimated chromosomes #library(SNPchip) #cc <- r$estPC #cc1 <- cc[chromosome(cc) == "2",1] #par(las=1) #plot(position(cc1), copyNumber(cc1)/100, ylim=c(-0.23, 0.1), ylab="copy number", xaxt="n") #plotIdiogram(2, build=genomeBuild(oligoSet), ylim=c(-0.225, -0.19), new=FALSE)