sigmashrink: Empirical Bayes shrinkage estimate of sigma^2

In ruv: Detect and Remove Unwanted Variation using Negative Controls

Description

This function (re)implements the empirical bayes shrinkage estimate of Smyth (2004), which is also implemented in the Limma package. This function is normally called from the function variance_adjust, and is not normally intended for stand-alone use.

Usage

sigmashrink(s2, d)

Arguments

s2	"Standard" estimates of sigma^2
d	"Standard" degrees of freedom of the residuals

Value

A list containing

sigma2	Estimates of sigma^2 using the empirical bayes shrinkage method of Smyth (2004)
df	Estimate of degrees of freedom using the empirical bayes shrinkage method of Smyth (2004)

Author(s)

Johann Gagnon-Bartsch [e-mail]

References

Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Smyth, 2004.

Using control genes to correct for unwanted variation in microarray data. Gagnon-Bartsch and Speed, 2012. Available at: http://biostatistics.oxfordjournals.org/content/13/3/539.full.

Removing Unwanted Variation from High Dimensional Data with Negative Controls. Gagnon-Bartsch, Jacob, and Speed, 2013. Available at: http://statistics.berkeley.edu/tech-reports/820.

See Also

variance_adjust

ruv documentation built on Aug. 31, 2019, 1:04 a.m.