comp.modt {DEDS}R Documentation

Computing Moderated t-statistics for Differential Expression


comp.modt returns a function of one argument with bindings for L. This function accepts a microarray data matrix as its single argment, when evaluated, computes moderated t-statistics by emprical Bayes shrinkage of the standard error toward a common value.


comp.modt(L = NULL)


L A vector of integers corresponding to observation (column) class labels. For k classes, the labels must be integers between 0 and k-1.


The function returned by comp.modt computes moderated t statistics for the assessment of differential expression. It interfaces to a C function. comp.stat is another function that wrapps around the same C function that could be used for computing moderated t statistics. For details of moderated statistics, see Smyth (2003).


comp.modt returns a function (F) with the bindings for L. The function F when supplied with a microarray data matrix and evaluated will return a numeric vector of moderated t statistics for each row of the matrix.


Yuanyuan Xiao,,
Jean Yee Hwa Yang,


Lönnstedt, I. and Speed, T. P. (2002). Replicated microarray data. Statistica Sinica 12, 31-46.

Smyth, G. K. (2003). Linear models and empirical Bayes methods for assessing differential expression in microarray experiments.

See Also

comp.FC, comp.t.


X <- matrix(rnorm(1000,0,0.5), nc=10)
L <- rep(0:1,c(5,5))

# genes 1-10 are differentially expressed

tmod <- comp.modt(L)
tmod.X <- tmod(X)

# Another way of computing moderated t statistics
tmod.X <- comp.stat(X, L, "modt")

[Package DEDS version 1.0.3 Index]