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.
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{
ho}^2_1})
estGlobParam(rec10k$log2ratio)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(mBPCR)
Loading required package: oligoClasses
Welcome to oligoClasses version 1.34.0
Loading required package: SNPchip
Welcome to SNPchip version 2.18.0
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/mBPCR/estGlobParam.Rd_%03d_medium.png", width=480, height=480)
> ### Name: estGlobParam
> ### Title: Estimate global parameters of copy number data
> ### Aliases: estGlobParam
> ### Keywords: univar
>
> ### ** Examples
>
> ##import the 10K data of cell line REC
> data(rec10k)
> ##estimation of all the global parameters (the variance of the segment is estimated with eqn{hat{
ho}^2_1})
> estGlobParam(rec10k$log2ratio)
Estimation of global parameters
$nu
[1] -0.02403854
$rhoSquare
[1] 0.08896371
$sigmaSquare
[1] 0.5971426
>
>
>
>
>
> dev.off()
null device
1
>
providing 
.