MCMC.qpcr: Bayesian Analysis of qRT-PCR Data
Version 1.2.3

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: .

Package details

AuthorMikhail V. Matz
Date of publication2016-11-09 23:56:55
MaintainerMikhail V. Matz <matz@utexas.edu>
LicenseGPL-3
Version1.2.3
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("MCMC.qpcr")

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MCMC.qpcr documentation built on May 30, 2017, 4:36 a.m.