padj.hpdsummary

hpdsumm

controls

<p>p-value correction method (see function p.adjust), default is Benjamini-Hochberg</p>

method

<p>Replaces raw p-values in an object returned by HPDsummary() 
by adjusted p-values corrected for multiple comparisons.
Disregards the entries corresponding to control genes.</p>

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>.

padj.hpdsummary: Adjusts p-values within an HPDsummary() object for multiple comparisons

Description

Usage

Arguments

Value

References