beckham.eff

amplification efficiencies for beckham.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>.

Mikhail Matz

MCMC.qpcr

Bayesian Analysis of qRT-PCR Data

beckham.eff function

A data frame with 11 observations on the following 2 variables.<dl class="dl-horizontal">
 <dt><code>gene</code></dt><dd>a factor with levels <code>atf</code> <code>dnaja4</code> <code>dnajb1</code> <code>dnajb4</code> <code>egr</code> <code>fos</code> <code>gadd</code> <code>gapdh</code> <code>hsp110</code> <code>hspb</code> <code>r18s</code></dd>
 <dt><code>eficiency</code></dt><dd>a numeric vector</dd>
 </dl>

Format

amplification efficiencies for beckham.data — beckham.eff

A data frame with 11 observations on the following 2 variables.<dl class='dl-horizontal'>
 <dt><code>gene</code></dt><dd>a factor with levels <code>atf</code> <code>dnaja4</code> <code>dnajb1</code> <code>dnajb4</code> <code>egr</code> <code>fos</code> <code>gadd</code> <code>gapdh</code> <code>hsp110</code> <code>hspb</code> <code>r18s</code></dd>
 <dt><code>eficiency</code></dt><dd>a numeric vector</dd>
 </dl>

beckham.eff: amplification efficiencies for beckham.data

Description

Usage

Arguments

Format

Examples