estGlobParam {mBPCR}R Documentation

Estimate global parameters of copy number data

Description

Function to estimate the global parameters of copy number data: the mean and the variance of the segment levels (called nu and rhoSquare, respectively), the variance of the noise (sigmaSquare). It is possible to choose the estimator of rhoSquare (i.e. either \hat{rho}_1^2 or \hat{rho}^2) and by default \hat{rho}_1^2 is used.

Usage

  estGlobParam(y, nu=NULL, rhoSquare=NULL, sigmaSquare=NULL, typeEstRho=1)

Arguments

y array containing the log2ratio of the copy number data
nu mean of the segment levels. If nu=NULL, then the algorithm estimates it on the sample.
rhoSquare variance of the segment levels. If rhoSquare=NULL, then the algorithm estimates it on the sample.
sigmaSquare variance of the noise. If sigmaSquare=NULL, then the algorithm estimates it on the sample.
typeEstRho choice of the estimator of rhoSquare. If typeEstRho=1, then the algorithm estimates rhoSquare with \hat{rho}_1^2, if typeEstRho=0 estimates it with \hat{rho}^2.

Value

A list cointaining nu, rhoSquare and sigmaSquare.

Examples

##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 all the global parameters (the variance of the segment is estimated with \hat{rho}^2_1)
estGlobParam(rec10k$logratio)


[Package mBPCR version 1.0 Index]