bg.mcmc {MBCB} | R Documentation |
This function provides the means of using only the MCMC (Bayesian) background correction method for the Illumina platform.
bg.mcmc(iter=500, burn=200)
iter |
The iteration count for the Baysian correction. |
burn |
The number of iterations to burn for the Bayesian correction. |
This function returns an array of alpha, mu, and sigma values representing the values computed during the mcmc trial.
This function makes use of two global variables. It will expect obsbead
and obsnc
are both established prior to calling this function. Obviously, this is not ideal, but R's pass-by-value functionality hindered the ability to pass these matrices as parameters. Using global variables increases performance substantially.
Yang Xie Yang.Xie@UTSouthwestern.edu, Min Chen min.chen@phd.mccombs.utexas.edu, Jeff Allen Jeffrey.Allen@UTSouthwestern.edu
data(MBCBExpressionData) # Use of global variables is obviously not ideal, but with R's pass-by-value # setup, we quickly run out of memory without using them on such large # arrays #all of the signals from sample #2 obsbead <<- expressionSignal[,2] #the negative control values for this sample obsnc <<- negativeControl[,2] #compute the alpha, mu, and sigma values bg.mcmc();