normalize.qpcr

data

Vector of control genes, such as 'controls=c("eif3h","nd5","rpl11")'

controls

Whether to perform centering around mean or not.

center

Performs multigene normalization as per Vandesompele et al 2002, centers the resulting gene expression values around the gene's means

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>.

normalize.qpcr: Internal function called by mcmc.qpcr.classic

Description

Usage

Arguments

Value

References