fitNull
fits the null distribution to a set of negative controls using Markov Chain Monte
Carlo (MCMC).
fitMcmcNull(logRr, seLogRr, iter = 1e+05)
A numeric vector of effect estimates on the log scale
The standard error of the log of the effect estimates. Hint: often the standard error = (log(<lower bound 95 percent confidence interval>) - log(<effect estimate>))/qnorm(0.025)
Number of iterations of the MCMC.
An object of type mcmcNull
containing the mean and standard deviation (both on the log
scale) of the null distribution, as well as the MCMC trace.
This is an experimental function for computing the 95 percent credible interval of a calibrated p-value using Markov-Chain Monte Carlo (MCMC).
if (FALSE) {
data(sccs)
negatives <- sccs[sccs$groundTruth == 0, ]
null <- fitMcmcNull(negatives$logRr, negatives$seLogRr)
null
plotMcmcTrace(null)
positive <- sccs[sccs$groundTruth == 1, ]
calibrateP(null, positive$logRr, positive$seLogRr)
}