These functions provide a simple interface to a variety of (regularized) t statistics
that are commonly used in the analysis of high-dimensional case-control studies.
data matrix. Note that the columns correspond to variables (“genes”)
and the rows to samples.
L
factor containing class labels for the two groups.
method
determines how the smoothing parameter is estimated (applies only to improved SAM statistic samL1).
plot
output diagnostic plot (applies only to improved SAM statistic samL1).
verbose
print out some (more or less useful) information during computation.
Details
efront.* computes the t statistic using the 90 % rule of Efron et al. (2001).
sam.* computes the SAM t statistic of Tusher et al. (2001).
Note that this requires the additional installation of the “samr” package.
samL1.* computes the improved SAM t statistic of Wu (2005).
Note that part of the code in this function is based on the R code providec
by B. Wu.
modt.* computes the moderated t statistic of Smyth (2004).
Note that this requires the additional installation of the “limma” package.
All the above statistics are compared relative to each other
and relative to the shrinkage t statistic in Opgen-Rhein and Strimmer (2007).
Value
The *.stat functions directly return the respective statistic for each variable.
The corresponding *.fun functions return a function that produces the respective
statistics when applied to a data matrix (this is very useful for simulations).
Opgen-Rhein, R., and K. Strimmer. 2007. Accurate ranking of
differentially expressed genes by a distribution-free shrinkage
approach.
Statist. Appl. Genet. Mol. Biol. 6:9.
(http://dx.doi.org/10.2202/1544-6115.1252)