MCMC.qpcr - Bayesian Analysis of qRT-PCR Data
Quantitative RT-PCR data are analyzed using generalized
linear mixed models based on lognormal-Poisson error
distribution, fitted using MCMC. Control genes are not required
but can be incorporated as Bayesian priors or, when template
abundances correlate with conditions, as trackers of global
effects (common to all genes). The package also implements a
lognormal model for higher-abundance data and a "classic" model
involving multi-gene normalization on a by-sample basis.
Several plotting functions are included to extract and
visualize results. The detailed tutorial is available here:
<https://matzlab.weebly.com/uploads/7/6/2/2/76229469/mcmc.qpcr.tutorial.v1.2.4.pdf>.
