comp.B {DEDS} | R Documentation |
comp.B
returns a function of one argument with bindings for
L
and proportion
. This function accepts a microarray
data matrix as its single argment, when evaluated, computes lod-odds
of differential expression by emprical Bayes shrinkage of the standard
error toward a common value. The lod-odds are sometimes called B
statistics.
comp.B(L = NULL, proportion = 0.01)
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. |
The function returned by comp.B
calculates B statistics for
each row of the microarray data matrix, with bindings for L
and
proportion
. It interfaces to a C function. comp.stat
is another function that wrapps around the same C function that could
be used for computing B statistics (see examples below).
comp.B
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 numeric vector of
B 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 # compute B statistics, proportion set as 0.01 B.fun <- comp.B(L) B.X <- B.fun(X) # compute B statistics, proportion set as 0.1 B.fun <- comp.B(L, proportion=0.1) B.X <- B.fun(X) # Another way of computing B statistics B.X<- comp.stat(X, L, "B")