comp.modt: Computing Moderated t-statistics for Differential Expression

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/DEDS.R

Description

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

Usage

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Arguments

L

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

Details

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 wraps around the same C function that could be used for computing moderated t statistics. For details of moderated statistics, see Smyth (2003).

Value

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.

Author(s)

Yuanyuan Xiao, [email protected],
Jean Yee Hwa Yang, [email protected].

References

Lonnstedt, 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. http://www.statsci.org/smyth/pubs/ebayes.pdf

See Also

comp.FC, comp.t.

Examples

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

# genes 1-10 are differentially expressed
X[1:10,6:10]<-X[1:10,6:10]+1

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

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

Bioconductor-mirror/DEDS documentation built on June 1, 2017, 5:11 p.m.