comp.modF {DEDS} | R Documentation |
comp.modF
returns a function of one argument with bindings for
L
. The function accepts a microarray data matrix as its single
argument, when evaluated, computes moderated F-statistics by emprical
Bayes shrinkage of the standard error toward a common value.
comp.modF(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.modF
computes moderated F
statistics for the assessment of differential expression. It
interfaces to a C function. comp.stat
is another
function that wrapps around the C function that could be used for
computing moderated F statistics. For details of moderated statistics,
see Smyth (2003).
comp.modF
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 F statistics
for each row of the matrix.
Yuanyuan Xiao, yxiao@itsa.ucsf.edu,
Jean Yee Hwa Yang, jean@biostat.ucsf.edu.
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. http://www.statsci.org/smyth/pubs/ebayes.pdf
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 fmod <- comp.modF(L) fmod.X <- fmod(X) # Another way of computing moderated F statistics fmod.X <- comp.stat(X, L, "modf")