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MCMC.qpcr  

Bayesian Analysis of qRT-PCR Data
View on CRAN: Click here


Download and install MCMC.qpcr package within the R console
Install from CRAN:
install.packages("MCMC.qpcr")

Install from Github:
library("remotes")
install_github("cran/MCMC.qpcr")

Install by package version:
library("remotes")
install_version("MCMC.qpcr", "1.2.4")



Attach the package and use:
library("MCMC.qpcr")
Maintained by
Mikhail V. Matz
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2013-09-28
Latest Update: 2020-03-29
Description:
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: .
How to cite:
Mikhail V. Matz (2013). MCMC.qpcr: Bayesian Analysis of qRT-PCR Data. R package version 1.2.4, https://cran.r-project.org/web/packages/MCMC.qpcr
Previous versions and publish date:
1.0.1 (2013-09-28 17:42), 1.0.2 (2014-01-04 04:19), 1.0.3 (2014-02-20 01:14), 1.0 (2013-07-23 08:29), 1.1.3 (2014-04-13 20:01), 1.1.5 (2015-01-27 23:04), 1.1.7 (2015-04-30 20:28), 1.2.2 (2015-10-28 08:44), 1.2.3 (2019-02-04 12:34), 1.2 (2015-05-23 08:42)
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