estGlobParam: Estimate global parameters of copy number data

In paolarancoita/mBPCR: Bayesian Piecewise Constant Regression for DNA copy number estimation

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{ρ}_1^2 or \hat{ρ}^2) and by default \hat{ρ}_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{ρ}_1^2, while if typeEstRho=0, it estimates rhoSquare with \hat{ρ}^2.

Value

A list containing:

nu
rhoSquare
sigmaSquare

References

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

Examples

##import the 10K data of cell line REC  
data(rec10k)
##estimation of all the global parameters (the variance of the segment is 
##estimated with \eqn{\hat{\rho}^2_1})
estGlobParam(rec10k$log2ratio)

paolarancoita/mBPCR documentation built on Jan. 12, 2020, 6:24 p.m.