DEDS (version 1.46.0)

comp.ebayes: Computing Empirical Bayes Statistics for Differential Expression

Description

comp.ebayes returns a function of one argument with bindings for L and proportion. This function accepts a microarray data matrix as its single argument, when evaluated, computes lod-odds (B statistics) and moderated t statistics of differential expression by empirical Bayes shrinkage of the standard error toward a common value.

Usage

comp.ebayes(L = NULL, proportion = 0.01)

Arguments

L

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

proportion

A numeric variable specifying the proportion of differential expression.

Value

comp.ebayes returns a function (F) with the bindings for L and proportion . The function F when supplied with a microarray data matrix and evaluated will return a matrix of two columns:

t

Moderated t statistics

B

B statistics (log-odds) of differential expression

Details

The function returned by comp.ebayes calculates B statistics and moderated t statistics for each row of the microarray data matrix, with bindings for L and proportion. It interfaces to a C function.

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.modt,comp.B.

Examples

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

# compute B and moderated t statistics, proportion set as 0.01
ebayes.fun <- comp.ebayes(L)
ebayes.X <- ebayes.fun(X)

# compute B and moderated t statistics, proportion set as 0.1
ebayes.fun <- comp.ebayes(L, proportion=0.1)
ebayes.X <- ebayes.fun(X)